Penggunaan regresi kuadrat terkecil parsial abstract
•
0 likes•380 views
This document discusses using partial least squares regression (PLS) to address collinearity problems in multiple regression analysis and apply it to rainfall prediction using Global Circulation Model (GCM) data. PLS regression is an iterative method that can be used to solve collinearity issues unlike other methods that have closed-form solutions. The model was built using GCM and rainfall data from 1996-2000 and validated on 2001 data. PLS analysis over several iterations found a PRESS value of 5.714.118 and R^2 of 0.669 at the third iteration, indicating the model with 3 components could explain 66.9% of the variance in the dependent variable. The optimal PLS model based on GCM data
Report
Share
Report
Share
Download to read offline
Recommended
A Novel Technique in Software Engineering for Building Scalable Large Paralle...
Parallel processing is the only alternative for meeting computational demand of scientific and technological advancement. Yet first few parallelized versions of a large application code- in the present case-a meteorological Global Circulation Model- are not usually optimal or efficient. Large size and complexity of the code cause making changes for efficient parallelization and further validation difficult. The paper presents some novel techniques to enable change of parallelization strategy keeping the correctness of the code under control throughout the modification.
Time_Series_Assignment
This document summarizes a time series analysis of airline sales data from 1949 to 1961 using SAS software to forecast sales for 1961. It describes preparing the data by checking for volatility, non-stationarity, and seasonality. Several ARIMA models were fitted and the best model with p=0 and q=3 was selected using error metrics. Forecasts were made for 1961 and graphically compared to actual sales, with the aim of predicting airline sales for planning purposes.
Uk Airports Forecasting
United Kingdom (U.K.) Airports:
A Short term forecast by setting a new rules for defining targets
Annually Forecast (LHR): The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. We implement two trend models by using Add a trend line in XLS sheet
Bi gaussianity and indicator variograms (2006)
Most popular simulation techniques are based on the assumption of Multivariate Gaussianity.
Normal Scores transform does not assure fulfilling of this condition.
In practice only bivariate Gaussianity is tested.
The most common test consists of comparing the experimental indicator direct variograms of the raw variable with the direct indicator variograms derived from the biGaussian distribution.
But, what about the indicator cross variograms?, How do they behave in relation to BiGaussianity?
Short-Haul Flights
Short-haul flights can be energy inefficient, and therefore costly. One company looked for an AI-driven solution.
3D Analyst - Watershed and Stream Network
A watershed is defined as the area of land that drains to a particular point along a stream. The boundary of a watershed is defined by the highest elevations surrounding the stream, and a drop of water falling outside this boundary will drain to another watershed. This document outlines steps to automatically delineate watershed areas and stream networks in ArcGIS using tools like flow direction, flow accumulation, and watershed. The process involves converting DEM data to raster format, removing sinks, and generating channels, stream links, and watersheds based on flow patterns and accumulation thresholds.
Searching for Dynamical Resemblance Between Time Series: A Method Based on No...
This document proposes a method to search for dynamical resemblance between time series based on nonlinear autoregressive models (NARMAX). It involves using NARMAX models to represent time series, estimating models on different data windows, and comparing the eigenvalue variations between models. As a case study, it applies this to monthly river flow data divided into windows. It finds the dynamics of windows 1 and 6 are similar based on linear model forecasts and the proposed NARMAX approach, suggesting a hidden periodic cycle in the data.
Sales Data Forecasting for Airline
This document discusses sales forecasting for an airline using time series modeling. It describes preparing the data by checking for volatility, non-stationarity, and seasonality. Several time series models are identified and compared using information criteria. The best model is found to be ARIMA(0,1,3) based on lowest MAPE error. Forecasts are generated for the next 12 months and graphically represented along with the actual historical sales values.
Recommended
A Novel Technique in Software Engineering for Building Scalable Large Paralle...
Parallel processing is the only alternative for meeting computational demand of scientific and technological advancement. Yet first few parallelized versions of a large application code- in the present case-a meteorological Global Circulation Model- are not usually optimal or efficient. Large size and complexity of the code cause making changes for efficient parallelization and further validation difficult. The paper presents some novel techniques to enable change of parallelization strategy keeping the correctness of the code under control throughout the modification.
Time_Series_Assignment
This document summarizes a time series analysis of airline sales data from 1949 to 1961 using SAS software to forecast sales for 1961. It describes preparing the data by checking for volatility, non-stationarity, and seasonality. Several ARIMA models were fitted and the best model with p=0 and q=3 was selected using error metrics. Forecasts were made for 1961 and graphically compared to actual sales, with the aim of predicting airline sales for planning purposes.
Uk Airports Forecasting
United Kingdom (U.K.) Airports:
A Short term forecast by setting a new rules for defining targets
Annually Forecast (LHR): The best way to set up annual target and minimize the data discrepancy is to address the data by two trend models using the concept of 12 rolling months. We implement two trend models by using Add a trend line in XLS sheet
Bi gaussianity and indicator variograms (2006)
Most popular simulation techniques are based on the assumption of Multivariate Gaussianity.
Normal Scores transform does not assure fulfilling of this condition.
In practice only bivariate Gaussianity is tested.
The most common test consists of comparing the experimental indicator direct variograms of the raw variable with the direct indicator variograms derived from the biGaussian distribution.
But, what about the indicator cross variograms?, How do they behave in relation to BiGaussianity?
Short-Haul Flights
Short-haul flights can be energy inefficient, and therefore costly. One company looked for an AI-driven solution.
3D Analyst - Watershed and Stream Network
A watershed is defined as the area of land that drains to a particular point along a stream. The boundary of a watershed is defined by the highest elevations surrounding the stream, and a drop of water falling outside this boundary will drain to another watershed. This document outlines steps to automatically delineate watershed areas and stream networks in ArcGIS using tools like flow direction, flow accumulation, and watershed. The process involves converting DEM data to raster format, removing sinks, and generating channels, stream links, and watersheds based on flow patterns and accumulation thresholds.
Searching for Dynamical Resemblance Between Time Series: A Method Based on No...
This document proposes a method to search for dynamical resemblance between time series based on nonlinear autoregressive models (NARMAX). It involves using NARMAX models to represent time series, estimating models on different data windows, and comparing the eigenvalue variations between models. As a case study, it applies this to monthly river flow data divided into windows. It finds the dynamics of windows 1 and 6 are similar based on linear model forecasts and the proposed NARMAX approach, suggesting a hidden periodic cycle in the data.
Sales Data Forecasting for Airline
This document discusses sales forecasting for an airline using time series modeling. It describes preparing the data by checking for volatility, non-stationarity, and seasonality. Several time series models are identified and compared using information criteria. The best model is found to be ARIMA(0,1,3) based on lowest MAPE error. Forecasts are generated for the next 12 months and graphically represented along with the actual historical sales values.
Presentation
The document outlines objectives to perform an uncertainty analysis of flood performance in the Timis Bega catchment, develop flood hazard maps for a 2005 extreme event, test a novel uncertainty analysis method, and study applying cloud computing to the modeling and analysis. It will use numerical modeling with HEC-HMS, HEC-RAS, and SOBEK software and uncertainty analysis methods like Bayesian and GLUE approaches to analyze reservoir and polder performance, develop lead time curves, and create flood hazard maps to improve flood management in the catchment. Cloud computing will also be explored to improve the uncertainty analysis for complex water systems.
Geomorphology Maps
New Geomorphologic Maps prepared using ArcGis and Matlab illustrate the surface morphology of Oum Bouaghi (Algeria) and their surrounding area
Sales forecasting of an airline company using time series analysis (1) (1)
The document describes using time series analysis in SAS to forecast airline sales for the year 1961 based on monthly sales data from 1949-1960. Key steps included: checking for non-stationarity and seasonality, transforming the data using logs, selecting a development and validation sample, identifying the best ARIMA model using minimum BIC and AIC/SBC averages, generating forecasts from multiple models and selecting the model with minimum MAPE, and producing a final forecast for 1961 sales.
Lid driven cavity flow simulation using CFD & MATLAB
Steady Incompressible Navier-Stokes equation on a uniform grid has been studied at various Reynolds number using CFD (Computational Fluid Dynamics). Present paper aim is to obtain the stream-function and velocity field in steady state using the finite difference formulation on momentum equations and continuity equation. Reynold number dominates the flow problem. Taylor’s series expansion has been used to convert the governing equations in the algebraic form using finite difference schemes. MATLAB has been used to draw to flow simulations inside the driven-cavity.
Resume_TroyBergin
Troy Bergin is seeking a position on a multidisciplinary team working on high performance aircraft and spacecraft. He has a 3.90 GPA in aerospace engineering and mathematics from Virginia Tech, where he is currently enrolled in advanced courses including aerodynamics, vehicle vibration and control, and astromechanics. His technical skills include finite element analysis software and programming languages. He has research experience performing finite element analysis and calculating sensitivity derivatives.
The Analogues R-Package - Ramirez-Villegas
The Analogues R-Package - Ramirez-VillegasCCAFS | CGIAR Research Program on Climate Change, Agriculture and Food Security
Presentation by Julian Ramirez-Villegas.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal. CFD simulation of Lid driven cavity flow
This project aims at simulating lid driven cavity flow problem using package MATLAB. Steady Incompressible Navier-Stokes equation with continuity equation will be studied at various Reynolds number. The main aim is to obtain the velocity field in steady state using the finite difference formulation on momentum equations and continuity equation. Reynold number is the pertinent parameter of the present study. Taylor’s series expansion has been used to convert the governing equations in the algebraic form using finite difference schemes.
Final Report
This document presents the results of computational fluid dynamics simulations of lid-driven cavity flow. It compares results from ANSYS Fluent to published results from Ghia et al. for Reynolds number 1. It also compares results from a user-developed fractional step method on a staggered grid to Ghia et al., showing good agreement. Additional simulations at Reynolds number 1000 show agreement with Ghia et al. for the lower Reynolds number simulations but poorer agreement for the higher Reynolds number case, likely due to differences in grid resolution between the studies.
Collart_Stacey_2016_Improved analytical flux surface
The document describes improved models for representing the shape of magnetic flux surfaces and calculating poloidal asymmetries in tokamak plasmas. An orthogonalized flux-surface aligned coordinate system is developed based on an asymmetric variation of the "Miller" flux surface model. This model provides a more accurate representation of flux surfaces compared to other models when applied to DIII-D discharge data. The momentum and continuity equations are used to develop a system of equations relating density, velocity, and potential asymmetries, and detailed calculations are performed for a DIII-D discharge using the new coordinate system. The improved flux surface model is found to significantly influence the calculated poloidal asymmetry results.
SCALABLE SEMI-SUPERVISED LEARNING BY EFFICIENT ANCHOR GRAPH REGULARIZATION
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
End semester examination | MTH 653A, IITK Integral Equation
The document is about an end semester examination for the course MTH 653A Integral Equations from 2017. It provides information on an exam being held for the integral equations course to conclude the semester. The exam code is MTH 653A and it focuses on evaluating students' understanding of integral equations through a series of assessment questions.
Aristotle boyd martin-peci_poster_2017
Poster based on research on investigating the non-linear response of a synchronous machine to variations in system parameters (torque and damping), demonstrating the existence of a bifurcation curve within the parameter space. Response was visualized using state space diagrams. This poster was presented at the Power and Energy Conference at the University of Illinois (PECI) in Spring 2017.
3D Watershed Celebes
This document outlines the steps to derive watersheds in Central Celebes, Indonesia from SRTM data using 3D modeling software and ArcGIS tools:
1) Load and preprocess SRTM data to create a DEM raster, including cropping, filling blanks, converting projections, and saving as a GeoTIFF.
2) Perform terrain analysis in ArcGIS to calculate flow direction, flow accumulation, stream definition, stream segmentation, and catchment grid delineation using the ArcHydro tools.
3) View the resulting watersheds and hydrological networks in 3D in ArcScene by setting the appropriate layer properties and vertical exaggeration.
Absorption factor method of radiation
This document describes the absorption factor method of radiation. It involves calculating the absorption factor Bij, which is the fraction of emitted energy from surface i that is absorbed by surface j. An algebraic equation is given relating Bij and the emitted energy Ei. The equations for determining Bij are linear and can be solved using various matrix methods. Once calculated, the absorption factors do not depend on surface temperature and can be used to determine radiative transport for a given geometry under different thermal conditions by writing new energy balance equations. However, the absorption factor method requires solving a larger system of equations than the more commonly used radiosity method.
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...National Cheng Kung University
1. The document discusses modeling turbidity (TB) in a reservoir using linear regression (LR) and geographically weighted regression (GWR). TB was measured at 10 observation points and estimated from satellite imagery reflectance data.
2. Both LR and GWR were used to model TB, with GWR producing estimates that exactly matched the observed TB values.
3. GWR coefficients were interpolated using inverse distance weighting to produce a continuous TB surface map for the entire reservoir area shown in the satellite image.Analyses of the Watershed Transform
This document provides an analysis of different approaches to computing the watershed transform in digital images. It discusses watershed transforms based on flooding, path-cost minimization, topology preservation, local conditions, and minimum spanning forests. For each approach, it describes the processing procedure, mathematical foundations, and classic algorithms. It aims to classify watershed transform algorithms according to criteria like solution uniqueness, topology preservation, and complexity. The document concludes by summarizing the approaches and discussing future work.
Time Series Analysis - Modeling and Forecasting
In this study, we have to project the airline travel for the next 12 months .The dataset used here is SASHELP.AIR which is Airline data and contains two variables – DATE and AIR( labeled as International Airline Travel).It contains the data from JAN 1949 to DEC 1960.
Distributed data fusion for multirobot search
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3eprojects.com
meteodynWT meso coupling downscaling regional planing
At present, with the development of wind power project in China, there are more and more projects located at the complex terrain and complex environment. At the same time, since the large planned area of project, the complex mountain area, and limited number of met mast, even without met mast, in order to the reliable development of the wind power project, it is important that how to do the wind resource assessment without actual measurement wind data and other conditions such as less reliable wind data, and the met mast was not considered representative. This paper will use the atmospheric model to do mesoscale simulation calculation of wind resources, and then combine with CFD technology to downscaling computation to get high resolution wind power assessment result. Finally, in order to confirm the validity of this application in the actual project, the comparison between calculation values and measurement values is carried out. The verification result through the actual data of different met mast shows that the wind resource assessment method which combines the CFD and mesoscale technologies is reliable. The main contribution of the article is to provide the reference model and approach for regional planning and large scale wind resource assessment when there isn’t enough adequate and effective wind data.
Forecasting Default Probabilities in Emerging Markets and Dynamical Regula...
The document discusses robust conic generalized partial linear models (RCGPLMs) and their application in forecasting default probabilities in emerging markets. It provides background on regression techniques like MARS and CMARS. It then introduces generalized linear models (GLMs) and generalized partial linear models (GPLMs), describing how conic GPLMs combine linear and nonlinear regression methods. The document outlines the development of robust conic GPLMs to account for uncertainty in input data, and provides examples of applying RCGPLMs to real-world default prediction problems.
GRADIENT OMISSIVE DESCENT IS A MINIMIZATION ALGORITHM
This article presents a promising new gradient-based backpropagation algorithm for multi-layer
feedforward networks. The method requires no manual selection of global hyperparameters and is capable
of dynamic local adaptations using only first-order information at a low computational cost. Its semistochastic nature makes it fit for mini-batch training and robust to different architecture choices and data
distributions. Experimental evidence shows that the proposed algorithm improves training in terms of both
convergence rate and speed as compared with other well known techniques.
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
Principal component analysis (PCA) is a widespread and widely used in various areas of science such as bioinformatics, econometrics, and chemometrics among others. Once that PCA is based in the eigenvalues and the eigenvectors which are a very weak approach to high dimension systems with degrees of sparsity and in these situations the PCA is no longer a recommended procedure. Sparsity is very common in near infrared spectroscopy due to the large number of spectra required and the water absorption broad bands what makes these spectra very similar and with heavy sparsity in matrix dataset, demoting the precision and accuracy, in the multivariate modeling and within projections of data matrix in smaller dimensions. To overcoming these shortcomings the LASSO, a not PCA based method, model was applied to a NIR spectra dataset from Biodiesel and its performance was, statistically, compared with traditional multivariate modeling such as PCR and PLSR.
More Related Content
What's hot
Presentation
The document outlines objectives to perform an uncertainty analysis of flood performance in the Timis Bega catchment, develop flood hazard maps for a 2005 extreme event, test a novel uncertainty analysis method, and study applying cloud computing to the modeling and analysis. It will use numerical modeling with HEC-HMS, HEC-RAS, and SOBEK software and uncertainty analysis methods like Bayesian and GLUE approaches to analyze reservoir and polder performance, develop lead time curves, and create flood hazard maps to improve flood management in the catchment. Cloud computing will also be explored to improve the uncertainty analysis for complex water systems.
Geomorphology Maps
New Geomorphologic Maps prepared using ArcGis and Matlab illustrate the surface morphology of Oum Bouaghi (Algeria) and their surrounding area
Sales forecasting of an airline company using time series analysis (1) (1)
The document describes using time series analysis in SAS to forecast airline sales for the year 1961 based on monthly sales data from 1949-1960. Key steps included: checking for non-stationarity and seasonality, transforming the data using logs, selecting a development and validation sample, identifying the best ARIMA model using minimum BIC and AIC/SBC averages, generating forecasts from multiple models and selecting the model with minimum MAPE, and producing a final forecast for 1961 sales.
Lid driven cavity flow simulation using CFD & MATLAB
Steady Incompressible Navier-Stokes equation on a uniform grid has been studied at various Reynolds number using CFD (Computational Fluid Dynamics). Present paper aim is to obtain the stream-function and velocity field in steady state using the finite difference formulation on momentum equations and continuity equation. Reynold number dominates the flow problem. Taylor’s series expansion has been used to convert the governing equations in the algebraic form using finite difference schemes. MATLAB has been used to draw to flow simulations inside the driven-cavity.
Resume_TroyBergin
Troy Bergin is seeking a position on a multidisciplinary team working on high performance aircraft and spacecraft. He has a 3.90 GPA in aerospace engineering and mathematics from Virginia Tech, where he is currently enrolled in advanced courses including aerodynamics, vehicle vibration and control, and astromechanics. His technical skills include finite element analysis software and programming languages. He has research experience performing finite element analysis and calculating sensitivity derivatives.
The Analogues R-Package - Ramirez-Villegas
The Analogues R-Package - Ramirez-VillegasCCAFS | CGIAR Research Program on Climate Change, Agriculture and Food Security
Presentation by Julian Ramirez-Villegas.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal. CFD simulation of Lid driven cavity flow
This project aims at simulating lid driven cavity flow problem using package MATLAB. Steady Incompressible Navier-Stokes equation with continuity equation will be studied at various Reynolds number. The main aim is to obtain the velocity field in steady state using the finite difference formulation on momentum equations and continuity equation. Reynold number is the pertinent parameter of the present study. Taylor’s series expansion has been used to convert the governing equations in the algebraic form using finite difference schemes.
Final Report
This document presents the results of computational fluid dynamics simulations of lid-driven cavity flow. It compares results from ANSYS Fluent to published results from Ghia et al. for Reynolds number 1. It also compares results from a user-developed fractional step method on a staggered grid to Ghia et al., showing good agreement. Additional simulations at Reynolds number 1000 show agreement with Ghia et al. for the lower Reynolds number simulations but poorer agreement for the higher Reynolds number case, likely due to differences in grid resolution between the studies.
Collart_Stacey_2016_Improved analytical flux surface
The document describes improved models for representing the shape of magnetic flux surfaces and calculating poloidal asymmetries in tokamak plasmas. An orthogonalized flux-surface aligned coordinate system is developed based on an asymmetric variation of the "Miller" flux surface model. This model provides a more accurate representation of flux surfaces compared to other models when applied to DIII-D discharge data. The momentum and continuity equations are used to develop a system of equations relating density, velocity, and potential asymmetries, and detailed calculations are performed for a DIII-D discharge using the new coordinate system. The improved flux surface model is found to significantly influence the calculated poloidal asymmetry results.
SCALABLE SEMI-SUPERVISED LEARNING BY EFFICIENT ANCHOR GRAPH REGULARIZATION
TO GET THIS PROJECT COMPLETE SOURCE ON SUPPORT WITH EXECUTION PLEASE CALL BELOW CONTACT DETAILS
MOBILE: 9791938249, 0413-2211159, WEB: WWW.NEXGENPROJECT.COM,WWW.FINALYEAR-IEEEPROJECTS.COM, EMAIL:Praveen@nexgenproject.com
NEXGEN TECHNOLOGY provides total software solutions to its customers. Apsys works closely with the customers to identify their business processes for computerization and help them implement state-of-the-art solutions. By identifying and enhancing their processes through information technology solutions. NEXGEN TECHNOLOGY help it customers optimally use their resources.
End semester examination | MTH 653A, IITK Integral Equation
The document is about an end semester examination for the course MTH 653A Integral Equations from 2017. It provides information on an exam being held for the integral equations course to conclude the semester. The exam code is MTH 653A and it focuses on evaluating students' understanding of integral equations through a series of assessment questions.
Aristotle boyd martin-peci_poster_2017
Poster based on research on investigating the non-linear response of a synchronous machine to variations in system parameters (torque and damping), demonstrating the existence of a bifurcation curve within the parameter space. Response was visualized using state space diagrams. This poster was presented at the Power and Energy Conference at the University of Illinois (PECI) in Spring 2017.
3D Watershed Celebes
This document outlines the steps to derive watersheds in Central Celebes, Indonesia from SRTM data using 3D modeling software and ArcGIS tools:
1) Load and preprocess SRTM data to create a DEM raster, including cropping, filling blanks, converting projections, and saving as a GeoTIFF.
2) Perform terrain analysis in ArcGIS to calculate flow direction, flow accumulation, stream definition, stream segmentation, and catchment grid delineation using the ArcHydro tools.
3) View the resulting watersheds and hydrological networks in 3D in ArcScene by setting the appropriate layer properties and vertical exaggeration.
Absorption factor method of radiation
This document describes the absorption factor method of radiation. It involves calculating the absorption factor Bij, which is the fraction of emitted energy from surface i that is absorbed by surface j. An algebraic equation is given relating Bij and the emitted energy Ei. The equations for determining Bij are linear and can be solved using various matrix methods. Once calculated, the absorption factors do not depend on surface temperature and can be used to determine radiative transport for a given geometry under different thermal conditions by writing new energy balance equations. However, the absorption factor method requires solving a larger system of equations than the more commonly used radiosity method.
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...National Cheng Kung University
1. The document discusses modeling turbidity (TB) in a reservoir using linear regression (LR) and geographically weighted regression (GWR). TB was measured at 10 observation points and estimated from satellite imagery reflectance data.
2. Both LR and GWR were used to model TB, with GWR producing estimates that exactly matched the observed TB values.
3. GWR coefficients were interpolated using inverse distance weighting to produce a continuous TB surface map for the entire reservoir area shown in the satellite image.Analyses of the Watershed Transform
This document provides an analysis of different approaches to computing the watershed transform in digital images. It discusses watershed transforms based on flooding, path-cost minimization, topology preservation, local conditions, and minimum spanning forests. For each approach, it describes the processing procedure, mathematical foundations, and classic algorithms. It aims to classify watershed transform algorithms according to criteria like solution uniqueness, topology preservation, and complexity. The document concludes by summarizing the approaches and discussing future work.
Time Series Analysis - Modeling and Forecasting
In this study, we have to project the airline travel for the next 12 months .The dataset used here is SASHELP.AIR which is Airline data and contains two variables – DATE and AIR( labeled as International Airline Travel).It contains the data from JAN 1949 to DEC 1960.
Distributed data fusion for multirobot search
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3eprojects.com
meteodynWT meso coupling downscaling regional planing
At present, with the development of wind power project in China, there are more and more projects located at the complex terrain and complex environment. At the same time, since the large planned area of project, the complex mountain area, and limited number of met mast, even without met mast, in order to the reliable development of the wind power project, it is important that how to do the wind resource assessment without actual measurement wind data and other conditions such as less reliable wind data, and the met mast was not considered representative. This paper will use the atmospheric model to do mesoscale simulation calculation of wind resources, and then combine with CFD technology to downscaling computation to get high resolution wind power assessment result. Finally, in order to confirm the validity of this application in the actual project, the comparison between calculation values and measurement values is carried out. The verification result through the actual data of different met mast shows that the wind resource assessment method which combines the CFD and mesoscale technologies is reliable. The main contribution of the article is to provide the reference model and approach for regional planning and large scale wind resource assessment when there isn’t enough adequate and effective wind data.
What's hot (19)
Sales forecasting of an airline company using time series analysis (1) (1)
Sales forecasting of an airline company using time series analysis (1) (1)
Lid driven cavity flow simulation using CFD & MATLAB
Lid driven cavity flow simulation using CFD & MATLAB
Collart_Stacey_2016_Improved analytical flux surface
Collart_Stacey_2016_Improved analytical flux surface
SCALABLE SEMI-SUPERVISED LEARNING BY EFFICIENT ANCHOR GRAPH REGULARIZATION
SCALABLE SEMI-SUPERVISED LEARNING BY EFFICIENT ANCHOR GRAPH REGULARIZATION
End semester examination | MTH 653A, IITK Integral Equation
End semester examination | MTH 653A, IITK Integral Equation
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...
The Turbidity (TB) Varies with Time And Space in The Reservoir Using GWR And ...
meteodynWT meso coupling downscaling regional planing
meteodynWT meso coupling downscaling regional planing
Similar to Penggunaan regresi kuadrat terkecil parsial abstract
Forecasting Default Probabilities in Emerging Markets and Dynamical Regula...
The document discusses robust conic generalized partial linear models (RCGPLMs) and their application in forecasting default probabilities in emerging markets. It provides background on regression techniques like MARS and CMARS. It then introduces generalized linear models (GLMs) and generalized partial linear models (GPLMs), describing how conic GPLMs combine linear and nonlinear regression methods. The document outlines the development of robust conic GPLMs to account for uncertainty in input data, and provides examples of applying RCGPLMs to real-world default prediction problems.
GRADIENT OMISSIVE DESCENT IS A MINIMIZATION ALGORITHM
This article presents a promising new gradient-based backpropagation algorithm for multi-layer
feedforward networks. The method requires no manual selection of global hyperparameters and is capable
of dynamic local adaptations using only first-order information at a low computational cost. Its semistochastic nature makes it fit for mini-batch training and robust to different architecture choices and data
distributions. Experimental evidence shows that the proposed algorithm improves training in terms of both
convergence rate and speed as compared with other well known techniques.
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
Principal component analysis (PCA) is a widespread and widely used in various areas of science such as bioinformatics, econometrics, and chemometrics among others. Once that PCA is based in the eigenvalues and the eigenvectors which are a very weak approach to high dimension systems with degrees of sparsity and in these situations the PCA is no longer a recommended procedure. Sparsity is very common in near infrared spectroscopy due to the large number of spectra required and the water absorption broad bands what makes these spectra very similar and with heavy sparsity in matrix dataset, demoting the precision and accuracy, in the multivariate modeling and within projections of data matrix in smaller dimensions. To overcoming these shortcomings the LASSO, a not PCA based method, model was applied to a NIR spectra dataset from Biodiesel and its performance was, statistically, compared with traditional multivariate modeling such as PCR and PLSR.
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
Principal component analysis (PCA) is a widespread and widely used in various areas of science such as
bioinformatics, econometrics, and chemometrics among others. Once that PCA is based in the
eigenvalues and the eigenvectors which are a very weak approach to high dimension systems with
degrees of sparsity and in these situations the PCA is no longer a recommended procedure. Sparsity is
very common in near infrared spectroscopy due to the large number of spectra required and the water
absorption broad bands what makes these spectra very similar and with heavy sparsity in matrix dataset,
demoting the precision and accuracy, in the multivariate modeling and within projections of data matrix
in smaller dimensions. To overcoming these shortcomings the LASSO, a not PCA based method, model
was applied to a NIR spectra dataset from Biodiesel and its performance was, statistically, compared
with traditional multivariate modeling such as PCR and PLSR.
Recursive
This document describes a new recursive Monte Carlo simulation algorithm called the Sampled Path Set Algorithm (SPSA) for modeling complex k-out-of-n reliability systems. The SPSA uses a graph representation of a reliability block diagram and recursively searches the graph to determine system response based on the system state vector at each simulation iteration, allowing modeling of systems with general component failure and repair distributions and large numbers of components. Existing methods for analyzing such systems using tie/cut sets have limitations as the number of sets grows non-linearly with increased system complexity. The SPSA provides a more efficient alternative with linear growth in processing and memory requirements.
The Gaussian Process Latent Variable Model (GPLVM)
This document provides an outline for a talk on Gaussian Process Latent Variable Models (GPLVM). It begins with an introduction to why latent variable models are useful for dimensionality reduction. It then defines latent variable models and shows their graphical model representation. The document reviews PCA and introduces probabilistic versions like Probabilistic PCA (PPCA) and Dual PPCA. It describes how GPLVM generalizes these approaches using Gaussian processes. Examples applying GPLVM to face and motion data are provided, along with practical tips and an overview of GPLVM variants.
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
- The document presents a comparison of LASSO modeling versus traditional PCA-based multivariate modeling methods like PCR and PLSR for analyzing near-infrared (NIR) spectroscopy data with high sparsity.
- NIR spectra of biodiesel samples with varying concentrations of animal fat biodiesel blended into diesel fuel were collected and preprocessed.
- LASSO modeling, which performs variable selection by shrinking some coefficient values exactly to zero, was applied to the NIR data and compared to PCR and PLSR models in terms of prediction accuracy.
- The results showed that the LASSO method was able to build a robust calibration model for determining animal fat biodiesel concentration that was less sensitive to the high s
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
The document summarizes a study that compares the LASSO modeling method to traditional PCA-based multivariate modeling methods (PCR and PLSR) for building calibration models to predict biodiesel quality using near-infrared (NIR) spectroscopy data. The LASSO method was able to better handle the heavy sparsity present in the NIR spectral data matrix. Models were built using each method to predict the percentage of animal fat biodiesel in diesel B20 fuel blends using a dataset of 100 NIR spectra. The LASSO method was shown to shrink some coefficient values exactly to zero, providing variable selection, and its performance was statistically comparable or better than PCR and PLSR for this application.
TurnerBottoneStanekNIPS2013
This document discusses using variational inference methods to perform online change point detection when the underlying model is not in the exponential family. Specifically:
- It develops variational approximations to the posterior on change point times for efficient inference when the underlying model, like a Rice distribution, does not have tractable posterior predictive distributions.
- It applies this methodology to radar tracking, using a Rice distribution to model signal-to-noise ratio features, and develops a variational method for inferring the parameters of the non-exponential Rice distribution online.
- It provides improvements to online variational inference that allow updating approximations efficiently as new data arrives, enabling the use of variational inference within the Bayesian online change point detection framework.
nazelan2017.pdf
The document presents a method for sensorless speed control of a permanent magnet synchronous motor (PMSM) using a model reference adaptive system (MRAS) with a multilayer perceptron (MLP) neural network. The MRAS uses the PMSM model as the reference model and a current model as the adjustable model. Error signals from comparing the models are fed into the MLP network. Particle swarm optimization (PSO) is used to optimize the MLP weights and biases to minimize errors. Simulation results show the proposed MLP-PSO method achieves better performance than a PI controller in terms of rise time, settling time, overshoot, and root mean square error for various speed and load conditions.
Validation Study of Dimensionality Reduction Impact on Breast Cancer Classifi...
A fundamental problem in machine learning is identifying the most representative subset of features from
which we can construct a predictive model for a classification task. This paper aims to present a validation
study of dimensionality reduction effect on the classification accuracy of mammographic images. The
studied dimensionality reduction methods were: locality-preserving projection (LPP), locally linear
embedding (LLE), Isometric Mapping (ISOMAP) and spectral regression (SR). We have achieved high
rates of classifications. In some combinations the classification rate was 100%. But in most of the cases the
classification rate is about 95%. It was also found that the classification rate increases with the size of the
reduced space and the optimal value of space dimension is 60. We proceeded to validate the obtained
results by measuring some validation indices such as: Xie-Beni index, Dun index and Alternative Dun
index. The measurement of these indices confirms that the optimal value of reduced space dimension is
d=60.
A Comparative study of locality Preserving Projection & Principle Component A...
The document compares the dimensionality reduction techniques of locality preserving projection (LPP) and principal component analysis (PCA) when used with logistic regression for classification. Five public datasets were used to evaluate the techniques. LPP was found to outperform PCA across all datasets and performance metrics by better preserving the local data structure, which is more important for classification than the global structure preserved by PCA. LPP achieved higher accuracy, sensitivity, specificity, precision, F-score, and area under the ROC curve than PCA for all datasets. The results indicate LPP is an effective dimensionality reduction method for classification tasks when local structure is significant.
Adaptive response surface by kriging using pilot points for structural reliab...
Structural reliability analysis aims to compute the probability of failure by considering system uncertainties. However, this approach may require very time-consuming computation and becomes impracticable for complex structures especially when complex computer analysis and simulation codes are involved such as finite element method. Approximation methods are widely used to build simplified approximations, or metamodels providing a surrogate model of the original codes. The most popular surrogate model is the response surface methodology, which typically employs second order polynomial approximation using least-squares regression techniques. Several authors have been used response surface methods in reliability analysis. However, another approximation method based on kriging approach has successfully applied in the field of deterministic optimization. Few studies have treated the use of kriging approximation in reliability analysis and reliability-based design optimization. In this paper, the kriging approximation is used an alternative to the traditional response surface method, to approximate the performance function of the reliability analysis. The main objective of this work is to develop an efficient global approximation while controlling the computational cost and accurate prediction. A pilot point method is proposed to the kriging approximation in order to increase the prior predictivity of the approximation, which the pilot points are good candidates for numerical simulation. In other words, the predictive quality of the initial kriging approximation is improved by adding adaptive information called “pilot points” in areas where the kriging variance is maximum. This methodology allows for an efficient modeling of highly non-linear responses, while the number of simulations is reduced compared to Latin Hypercubes approach. Numerical examples show the efficiency and the interest of the proposed method.
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...International Journal of Science and Research (IJSR)
Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. The purpose of this paper is the level set approach to simultaneous tissue segmentation and bias correction of Magnetic Resonance Imaging (MRI) images. A modified level set approach to joint segmentation and bias correction of images with intensity in homogeneity. A sliding window is used to transform the gradient intensity domain to another domain, where the distribution overlap between different tissues is significantly suppressed. Tissue segmentation and bias correction are simultaneously achieved via a multiphase level set evolution process. The proposed methods are very robust to initialization, and are directly compatible with any type of level set implementation. Experiments on images of various modalities demonstrated the superior performance over state-of-the-art methods.
IRJET- A Comparative Forecasting Analysis of ARIMA Model Vs Random Forest Alg...
This document presents a comparative analysis of forecasting energy demand using two different methods: an ARIMA time series model and a Random Forest machine learning algorithm. Both methods are applied to monthly and yearly timespan data from a small-scale industrial load dataset. The accuracy of forecasts from each method is compared. The document provides background on the importance of energy forecasting for power grid management. It also describes the ARIMA and Random Forest models in more detail for short-term and long-term load forecasting.
Acceleration of the Longwave Rapid Radiative Transfer Module using GPGPU
This poster presents Weather Research and Forecast (WRF)
model is a next-generation mesoscale numerical weather
prediction system designed to serve both operational forecasting
and atmospheric research communities. WRF offers multiple
physics options, one of which is the Long-Wave Rapid Radiative
Transfer Model (RRTM). Even with the advent of large-scale
parallelism in weather models, much of the performance increase
has came from increasing processor speed rather than increased
parallelism. We present an alternative method of scaling model
performance by exploiting emerging architectures like GPGPU
using the fine-grain parallelism. We claim to get much more than
23.71x, performance gain by using asynchronous data transfer,
use of texture memory and the techniques like loop unrolling.
International Journal of Engineering Research and Development
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
S4101116121
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
2006.11583.pdf
The document proposes an Attention Temporal Graph Convolutional Network (A3T-GCN) model for traffic forecasting that aims to simultaneously capture global temporal dynamics and spatial correlations in traffic data. The A3T-GCN combines a Graph Convolutional Network (GCN) to learn spatial dependencies based on road network topology with a Gated Recurrent Unit (GRU) to learn temporal trends, and introduces an attention mechanism to adjust the importance of different time points and better predict traffic. Experimental results on real-world datasets demonstrate the effectiveness of the proposed A3T-GCN model.
Testing the performance of the power law process model considering the use of...
Within the class of non-homogeneous Poisson process (NHPP) models and as a result of the simplicity of
the mathematical computations of the Power Law Process (PLP) model and the attractive physical
explanation of its parameters, this model has found considerable attention in repairable systems literature.
In this article, we conduct the investigation of new estimation approach, the regression estimation
procedure, on the performance of the parametric PLP model. The regression approach for estimating the
unknown parameters of the PLP model through the mean time between failure (TBF) function is evaluated
against the maximum likelihood estimation (MLE) approach. The results from the regression and MLE
approaches are compared based on three error evaluation criteria in terms of parameter estimation and its
precision, the numerical application shows the effectiveness of the regression estimation approach at
enhancing the predictive accuracy of the TBF measure.
Similar to Penggunaan regresi kuadrat terkecil parsial abstract (20)
Forecasting Default Probabilities in Emerging Markets and Dynamical Regula...
Forecasting Default Probabilities in Emerging Markets and Dynamical Regula...
GRADIENT OMISSIVE DESCENT IS A MINIMIZATION ALGORITHM
GRADIENT OMISSIVE DESCENT IS A MINIMIZATION ALGORITHM
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
The Gaussian Process Latent Variable Model (GPLVM)
The Gaussian Process Latent Variable Model (GPLVM)
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
LASSO MODELING AS AN ALTERNATIVE TO PCA BASED MULTIVARIATE MODELS TO SYSTEM W...
Validation Study of Dimensionality Reduction Impact on Breast Cancer Classifi...
Validation Study of Dimensionality Reduction Impact on Breast Cancer Classifi...
A Comparative study of locality Preserving Projection & Principle Component A...
A Comparative study of locality Preserving Projection & Principle Component A...
Adaptive response surface by kriging using pilot points for structural reliab...
Adaptive response surface by kriging using pilot points for structural reliab...
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...
IRJET- A Comparative Forecasting Analysis of ARIMA Model Vs Random Forest Alg...
IRJET- A Comparative Forecasting Analysis of ARIMA Model Vs Random Forest Alg...
Acceleration of the Longwave Rapid Radiative Transfer Module using GPGPU
Acceleration of the Longwave Rapid Radiative Transfer Module using GPGPU
International Journal of Engineering Research and Development
International Journal of Engineering Research and Development
Testing the performance of the power law process model considering the use of...
Testing the performance of the power law process model considering the use of...
More from Gusti Rusmayadi
Ii pendahahuluan atmosfer
Atmosfer terdiri dari gas, cairan, dan aerosol yang tersebar di berbagai ketinggian. Terdapat 4 lapisan utama atmosfer yaitu troposfer, stratosfer, mesosfer, dan termosfer. Atmosfer berperan sebagai sumber gas dan air hujan, filter sinar matahari, dan penyangga suhu bumi. Pembentukan cuaca dan iklim dipengaruhi oleh radiasi matahari, suhu, tekanan udara, dan angin. Lapisan ozon di stratosfer melindungi b
IX evapotranspirasi
Dokumen tersebut membahas tentang evapotranspirasi yang merupakan proses penguapan air dari permukaan tanah dan transpirasi air dari tanaman. Beberapa faktor yang mempengaruhi evapotranspirasi dijelaskan seperti faktor iklim, geografi, dan lainnya. Berbagai metode pengukuran evapotranspirasi secara langsung dan tidak langsung juga diuraikan.
viii hujan
Materi ini membicarakan kejadian hujan dan tipe hujan serta pengukuran dan analis data hujan
Vii angin
Ringkasan dokumen tersebut adalah:
1. Dokumen tersebut membahas tentang tiga hukum gerak Newton dan gaya-gaya yang mempengaruhi aliran angin, termasuk gaya gradien tekanan, gaya Coriolis, dan gaya gesekan.
2. Dibahas pula sistem sirkulasi angin dunia yang terdiri atas angin pasat, baratan, dan jet stream, serta angin lokal seperti angin darat, laut, gunung, dan lembah.
3.
Vi tekanan udara
Dokumen ini membahas tentang tekanan udara, termasuk pengertian, persamaan hidrostatika, hukum-hukum gas, variasi tekanan secara vertikal dan horizontal, pengukuran tekanan, serta istilah terkait tekanan udara.
Leaflet ps agronomi 2014
Tahun 2014 Program Studi Agronomi menerima kembali mahasiswa baru melalui Jalur SBMPTN dan Jalur Mandiri (Senyum). Kode Pilihan PS Agronomi adalah : 751372 AGRONOMI
Pemodelan produksi gtr 2013
1. Model ini memprediksi produksi biomassa potensial dan aktual tanaman dengan mempertimbangkan faktor-faktor lingkungan seperti radiasi matahari, suhu, dan indeks luas daun.
2. Produksi biomassa dihitung berdasarkan laju fotosintesis, respirasi, dan efisiensi penggunaan radiasi yang dipengaruhi karakteristik daun tanaman.
3. Model ini dapat digunakan untuk memprediksi hasil berbagai jenis tanaman di berbagai
Susi 28-36
Teks tersebut membahas komposisi kimia dan asam amino pada tempe kacang nagara (Vigna unguiculata ssp. cylindrica). Penelitian ini mengkaji kualitas gizi dan komposisi asam amino pada tempe kacang nagara dengan variasi waktu fermentasi 36, 42, dan 48 jam. Hasilnya menunjukkan bahwa fermentasi selama 36 jam memberikan kualitas gizi terbaik dengan kadar protein 25,37%, lemak 4,23%, dan karbohidrat 59
Zuraida titi-22-27
Studi ini mengkaji populasi bakteri Thiobacillus sp. dan Thiobacillus ferrooxidans pada tanah sulfat masam setelah perlakuan penggenangan dan pengeringan. Hasilnya menunjukkan populasi bakteri tersebut berkisar antara 1,5x10^14-2,5x10^14 sel/g tanah untuk Thiobacillus sp. dan 8,33x10^6-2x10^7 sel/g tanah untuk T. ferrooxidans. Populasi tertinggi ditemukan pada perlak
Habibah baik11-14
Ringkasan dokumen tersebut adalah:
1. Penelitian ini bertujuan untuk mengetahui perubahan kadar protein dan pH susu pasteurisasi selama penyimpanan dingin.
2. Kadar protein susu menurun seiring bertambahnya lama penyimpanan akibat pertumbuhan mikroba.
3. pH susu pasteurisasi masih dalam standar SNI meski mengalami perubahan selama pengolahan dan penyimpanan.
Model simulasi antrian gtr
Materi Pengantar Analisis Sistem untuk PS Teknologi Industri Pertanian Faperta Unlam
Simulasi monte carlo gtr
Dokumen tersebut membahas tentang simulasi Monte Carlo. Metode ini digunakan untuk menyelesaikan masalah yang sulit diselesaikan secara analitis dengan mengambil sampel acak berulang kali. Contoh penggunaannya adalah memprediksi pola permintaan sendal selama 20 hari berikutnya dengan mengacak angka permintaan harian berdasarkan data sebelumnya. Metode ini juga digunakan untuk menguji generator bilangan acak dengan menghitung stat
More from Gusti Rusmayadi (20)
Recently uploaded
Skybuffer SAM4U tool for SAP license adoption
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
OpenID AuthZEN Interop Read Out - Authorization
During Identiverse 2024 and EIC 2024, members of the OpenID AuthZEN WG got together and demoed their authorization endpoints conforming to the AuthZEN API
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
How to Get CNIC Information System with Paksim Ga.pptx
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Recently uploaded (20)
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Choosing The Best AWS Service For Your Website + API.pptx
Choosing The Best AWS Service For Your Website + API.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Nordic Marketo Engage User Group_June 13_ 2024.pptx
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Best 20 SEO Techniques To Improve Website Visibility In SERP
Best 20 SEO Techniques To Improve Website Visibility In SERP
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
20240609 QFM020 Irresponsible AI Reading List May 2024
20240609 QFM020 Irresponsible AI Reading List May 2024
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
Penggunaan regresi kuadrat terkecil parsial abstract
- 1. PENGGUNAAN REGRESI KUADRAT TERKECIL PARSIAL (PLS) UNTUK MENGATASI KOLINIERITAS DAN PEMANFAATANNYA UNTUK PREDIKSI CURAH HUJAN BERDASARKAN DATA GCM (Global Circulation Model) Oleh: GUSTI RUSMAYADI1 dan UMI SALAWATI2 ABSTRACT Prediction of parameter in multiple regression analysis is interesting topics of some research. It can because of some problems in rising at regression that is colinierity problem. Some of methods that used to solve colinierity problem is using principle component regression (PCR), ridge regression and partial least square (PLS). The regression coefficient of PLS can be find iteratively and it has not closed formula to search variant of regression coefficient. GCM data in grid V2272 – V2727 in years 1996 – 2001 and rainfall data from BMKG station (310L Sta) in 1996-2001. The 1996 – 2000 data was used to building model, beside it 2001 data was used to model validated. All of calculation and graph were used Minitab® software on 14.12 versions and Microsoft Excel®. Estimating based on PLS algebra at some iterations have result PRESS value and R2. Varian of X variable with 3 components of model can explain about 66.9% in variant of dependent variable. Minimal PRESS in 5.714.118 value is get at the third iterations with R2 higher at 7%. Analysis of regression with PLS methods to GCM and rainfall data or it was known as statistical downscaling, get prediction value regression model at the third levels. The model can used to prediction rainfall as long as 12 months and it was validated. The optimal PLS based on GCM data can be used to prediction local rainfall. The next research should to used period data GCM and rainfall so can be used to predict period event too, DJF periods for example. Keyword: PLS, PRESS, colinierity, iteration 1 Staf Pengajar pada Jurusan Budidaya Pertanian Faperta UNLAM 2 Staf Pengajar pada Jurusan Sosial Ekonomi Pertanian Faperta UNLAM