shrinkage-parameters-for-each-explanatory-variable-found-via-particle-swarm-optimization-in-ridge-regression-peertechz-journal-of-computer-science-and-engineering-peertechz-journals
•Download as PPTX, PDF•
0 likes•48 views
Ridge regression method is an improved method when the assumptions of independence of the explanatory variables cannot be achieved, which is also called multicollinearity problem, in regression analysis. ...
Report
Share
Report
Share
Recommended
Isochrone fitting and Gaia results
1) The document describes a tool called UniDAM that performs isochrone fitting to estimate stellar parameters like distance, age, and mass from photometric and spectroscopic data.
2) UniDAM fits probability density functions and provides quality flags, correlations between parameters, and open source flexibility. It uses only infrared photometry to minimize extinction effects.
3) The author has applied UniDAM to data from various surveys along with Gaia parallaxes, producing a catalog of distances, ages, and masses for 5.5 million stars.
Transformasi Data Penelitian
Artikel mengenai berbagai teknik transformasi data penelitian agar memenuhi persyaratan asumsi klasik normalitas.
MEng Dissertation Abstract
This document summarizes a study that performed incremental dynamic analysis on steel moment frames using 8 real earthquake ground motions scaled from 0.05g to 6g. Three frame models were analyzed: 1) a bilinear model with 3% hardening and without geometric nonlinearities, 2) the same bilinear model but with geometric nonlinearities, and 3) a model with cyclic degradation and P-Delta effects. The goal was to identify the most important design parameter for these frames by examining strength reduction, overstrength factors, and collapse mechanisms under different ductility demands. Statistical tools and automated programming were used to analyze the results, assess frame vulnerability, and predict potential financial losses.
Least action parametric quantification of ad na k at-pase in e-e compensation
1) The document discusses Gibbs molar action and its relation to enzyme kinetics formulas involving rate constants and Gibbs free energy.
2) It references the work of scientists who studied homeokinetics and homeodynamics as related to enzyme action.
3) The document includes a figure from a study comparing the temperature dependence of Na,K-ATPase activity in Alzheimer's disease and control brain tissue membranes.
Factor of reliability, fragility and probability of
This document discusses uncertainties in reliability analysis and how they affect the probability of failure. It defines probability of failure as the probability that the load will exceed resistance. While higher safety factors are intended to lower probability of failure, uncertainties can prevent this. The conditional probability of failure and fragility analysis are introduced to evaluate probability of failure given load levels. The Drucker-Prager theory for nonlinear analysis is also summarized, which uses an elasto-plastic yield criterion defined by invariants of the stress tensor and material properties of cohesion and friction angle.
Spectroscopic Investigation of Charge Transfer Complexes of 4-Aminoacetanilid...
Spectroscopic Investigation of Charge Transfer Complexes of 4-Aminoacetanilid...Association of Scientists, Developers and Faculties
The molecular complexes of a series of electron acceptors of 1,4-benzoquinone (BQ), 2,3,5,6-tetrachloro-1,4-benzoquinone (CHL) and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) with 4-aminoacetanilide (ACE) have been investigated using various spectral techniques. The stoichiometry of the complexes was determined by photometric titration method and was found to be 1:1, in all the cases. The results of equilibrium and kinetic studies were performed and the final interaction products were characterized by FT-IR.Rate of Reactions
Rate of a chemical reaction is discussed in these slides.Mainly it has been concentrated on Rate Laws and factors affecting the Rate of Reaction
PUR Abstract
This research aims to accurately measure the injection angle and plume length of fuel entering a small diesel engine's combustion chamber using high-speed imaging. Water mixed with dye will be injected into a pressurized polycarbonate replica of the chamber using the engine-driven fuel injector. High-speed video will be analyzed with MATLAB to generate a 3D model of the injection process. The goal is to determine the relationship between harmful diesel combustion particles and properties of the fuel injection.
Recommended
Isochrone fitting and Gaia results
1) The document describes a tool called UniDAM that performs isochrone fitting to estimate stellar parameters like distance, age, and mass from photometric and spectroscopic data.
2) UniDAM fits probability density functions and provides quality flags, correlations between parameters, and open source flexibility. It uses only infrared photometry to minimize extinction effects.
3) The author has applied UniDAM to data from various surveys along with Gaia parallaxes, producing a catalog of distances, ages, and masses for 5.5 million stars.
Transformasi Data Penelitian
Artikel mengenai berbagai teknik transformasi data penelitian agar memenuhi persyaratan asumsi klasik normalitas.
MEng Dissertation Abstract
This document summarizes a study that performed incremental dynamic analysis on steel moment frames using 8 real earthquake ground motions scaled from 0.05g to 6g. Three frame models were analyzed: 1) a bilinear model with 3% hardening and without geometric nonlinearities, 2) the same bilinear model but with geometric nonlinearities, and 3) a model with cyclic degradation and P-Delta effects. The goal was to identify the most important design parameter for these frames by examining strength reduction, overstrength factors, and collapse mechanisms under different ductility demands. Statistical tools and automated programming were used to analyze the results, assess frame vulnerability, and predict potential financial losses.
Least action parametric quantification of ad na k at-pase in e-e compensation
1) The document discusses Gibbs molar action and its relation to enzyme kinetics formulas involving rate constants and Gibbs free energy.
2) It references the work of scientists who studied homeokinetics and homeodynamics as related to enzyme action.
3) The document includes a figure from a study comparing the temperature dependence of Na,K-ATPase activity in Alzheimer's disease and control brain tissue membranes.
Factor of reliability, fragility and probability of
This document discusses uncertainties in reliability analysis and how they affect the probability of failure. It defines probability of failure as the probability that the load will exceed resistance. While higher safety factors are intended to lower probability of failure, uncertainties can prevent this. The conditional probability of failure and fragility analysis are introduced to evaluate probability of failure given load levels. The Drucker-Prager theory for nonlinear analysis is also summarized, which uses an elasto-plastic yield criterion defined by invariants of the stress tensor and material properties of cohesion and friction angle.
Spectroscopic Investigation of Charge Transfer Complexes of 4-Aminoacetanilid...
Spectroscopic Investigation of Charge Transfer Complexes of 4-Aminoacetanilid...Association of Scientists, Developers and Faculties
The molecular complexes of a series of electron acceptors of 1,4-benzoquinone (BQ), 2,3,5,6-tetrachloro-1,4-benzoquinone (CHL) and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) with 4-aminoacetanilide (ACE) have been investigated using various spectral techniques. The stoichiometry of the complexes was determined by photometric titration method and was found to be 1:1, in all the cases. The results of equilibrium and kinetic studies were performed and the final interaction products were characterized by FT-IR.Rate of Reactions
Rate of a chemical reaction is discussed in these slides.Mainly it has been concentrated on Rate Laws and factors affecting the Rate of Reaction
PUR Abstract
This research aims to accurately measure the injection angle and plume length of fuel entering a small diesel engine's combustion chamber using high-speed imaging. Water mixed with dye will be injected into a pressurized polycarbonate replica of the chamber using the engine-driven fuel injector. High-speed video will be analyzed with MATLAB to generate a 3D model of the injection process. The goal is to determine the relationship between harmful diesel combustion particles and properties of the fuel injection.
Trends in Computer Science and Information Technology
This document summarizes a research article about using particle swarm optimization to find different shrinkage parameters (k values) for each explanatory variable in ridge regression, rather than a single k value. Ridge regression is used to address multicollinearity issues in multiple regression analysis. Typically, ridge regression estimates a single k value, but this study uses an algorithm based on particle swarm optimization to estimate different k values for each variable. The study applies this new method to real data and simulations to evaluate its performance compared to other ridge regression methods.
Particle Swarm Optimization based K-Prototype Clustering Algorithm
This document summarizes a research paper that proposes a new Particle Swarm Optimization (PSO) based K-Prototype clustering algorithm to cluster mixed numeric and categorical data. It begins with background information on clustering algorithms like K-Means, K-Modes, and K-Prototype. It then describes the K-Prototype algorithm, PSO, and discrete binary PSO. Related work integrating PSO with other clustering algorithms is also reviewed. The proposed approach uses binary PSO to select improved initial prototypes for K-Prototype clustering in order to obtain better clustering results than traditional K-Prototype and avoid local optima.
I017235662
This document discusses using particle swarm optimization to improve the k-prototype clustering algorithm. The k-prototype algorithm clusters data with both numeric and categorical attributes but can get stuck in local optima. The proposed method uses particle swarm optimization, a global optimization technique, to guide the k-prototype algorithm towards better clusterings. Particle swarm optimization models potential solutions as particles that explore the search space. It is integrated with k-prototype clustering to avoid locally optimal solutions and produce better clusterings. The method is tested on standard benchmark datasets and shown to outperform traditional k-modes and k-prototype clustering algorithms.
Using particle swarm optimization to solve test functions problems
In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
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.
4 tracking objects of deformable shapes
The document describes a method for tracking objects of deformable shapes in images. It proposes representing the matching of a deformable template to an image as a minimum cost cyclic path in a product space of the template and image. An energy functional is introduced that consists of a data term favoring strong image gradients, a shape consistency term favoring similar tangent angles, and an elastic penalty. Optimization is performed using a minimum ratio cycle algorithm parallelized on GPUs. This provides efficient, pixel-accurate segmentation and correspondence between template and image curve. The method can be extended to 4D to segment and track multiple deformable anatomical structures in medical images.
Numerical modeling to evaluate pile head deflection under the lateral load
Abstract The complex behavior of pile head deflection under the lateral load can be studied using various analytical methods and the softwares. Often the lateral pile load testing is carried out in the field to confirm the calculated lateral pile capacity. However, even with the use of sophisticated latest softwares, the accurate deflection of pile head cannot be estimated. Hence an attempt has been made in this paper to evaluate the pile head deflection using the field load-deflection data and the corresponding soil and pile properties. A preliminary mathematical model has been developed using a technique of dimensional analysis (DA) to evaluate pile head deflection under different pile diameters, different pile materials and varying soil conditions. The estimated pile head deflection using DA equation is compared with 14nos. of measured lateral pile load test results conducted at the site. It can be observed from this study that, the dimensional analysis can be used effectively to estimate the pile head deflection. More variables based on more field results can be introduced in the mathematical model to increase the accuracy in the estimation of pile head deflection. Keywords: Pile head deflection, Lateral pile load, Dimensional analysis
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...International Journal of Science and Research (IJSR)
This paper discusses the possible applications of particle swarm optimization (PSO) in the Power system. One of the problems in Power System is Economic Load dispatch (ED). The discussion is carried out in view of the saving money, computational speed – up and expandability that can be achieved by using PSO method. The general approach of the method of this paper is that of Dynamic Programming Method coupled with PSO method. The feasibility of the proposed method is demonstrated, and it is compared with the lambda iterative method in terms of the solution quality and computation efficiency. The experimental results show that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently in ED problems.
Calculation of solar radiation by using regression methods
Abstract. In this study, solar radiation was estimated at 53 location over Turkey with
varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN
and Gaussian process regression methods. The data of 2002 and 2003 years were used to
obtain regression coefficients of relevant methods. The coefficients were obtained based on
the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface
temperature (LST).The values for LST were obtained from the data of the National
Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer
(NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in
regression methods for 2004 year. The results were compared statistically. The most
successful method was Gaussian process regression method. The most unsuccessful method
was lasso regression method. While means bias error (MBE) value of Gaussian process
regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was
calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as
0,941. Statistical results are consistent with the literature. Used the Gaussian process
regression method is recommended for other studies.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...Nooria Sukmaningtyas
Making full use of abundant renewable solar energy through the development of photovoltaic (PV)
technology is an effective means to solve the problems such as difficulty in electricity supply and energy
shortages in remote rural areas. In order to improve the electricity generating efficiency of PV cells, it is
necessary to track the maximum power point of PV array, which is difficult to make under partially shaded
conditions due to the odds of the appearance of two or more local maximum power points., In this paper, a
control algorithm of maximum power point tracking (MPPT) based on improved particle swarm optimization
(IPSO) algorithm is presented for PV systems. Firstly, the current in maximum power point is searched
with the IPSO algorithm, and then the real maximum power point is tracked through controlling the output
current of PV array. The MPPT method based on IPSO algorithm is established and simulated with Matlab
/ Simulink, and meanwhile, the comparison between IPSO MPPT algorithm and traditional MPPT algorithm
is also performed in this paper. It is proved through simulation and experimental results that the IPSO
algorithm has good performances and very fast response even to partial shaded PV modules, , which
ensures the stability of PV system.Ds33717725
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Ds33717725
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Ap33243246
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Ap33243246
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A Combined Entropy-FR Weightage Formulation Model for Delineation of Groundwa...
This document presents a study that develops a combined entropy-frequency ratio (FR) weightage formulation model to delineate groundwater potential zones. Digital elevation models and satellite imagery are used to prepare thematic maps of factors like slope and rainfall. These maps are divided into classes and their pixel counts are calculated to determine area percentages. Frequency ratios are then calculated comparing area percentages of each class to the total area. Entropy and information coefficients are also calculated. Finally, weights are assigned to each class for each thematic map by combining the entropy and FR values using the proposed entropy-FR model. This provides objective weights to replace subjective weights. The weighted thematic maps are then overlaid to produce a composite groundwater potential zones map. The
3 article azojete vol 7 24 33
This document discusses using a particle swarm optimization algorithm to solve the K-node set reliability optimization problem for distributed computing systems. The K-node set reliability optimization problem aims to maximize the reliability of a subset of k nodes in a distributed computing system while satisfying a specified capacity constraint. It presents the problem formulation and describes particle swarm optimization, a metaheuristic optimization technique inspired by swarm intelligence. The proposed algorithm applies a discrete particle swarm optimization approach to solve the K-node set reliability optimization problem, which is demonstrated on an example distributed computing system topology.
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...CrimsonPublishersRDMS
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Study on the Uniqueness of Inverse Solutions by Fabian Pöhl* in Crimson Publishers: Peer Reviewed Material Science JournalsThe inverse scattering series for tasks associated with primaries: direct non...
The inverse scattering series for tasks associated with primaries: direct non-linear inversion of 1D elastic media. In this paper, research on direct inversion for two pa-
rameter acoustic media (Zhang and Weglein, 2005) is
extended to the three parameter elastic case. We present
the first set of direct non-linear inversion equations for
1D elastic media (i.e., depth varying P-velocity, shear
velocity and density). The terms for moving mislocated
reflectors are shown to be separable from amplitude
correction terms. Although in principle this direct
inversion approach requires all four components of elastic
data, synthetic tests indicate that consistent value-added
results may be achieved given only ˆDPP measurements.
We can reasonably infer that further value would derive
from actually measuring ˆDPP , ˆD PS, ˆDSP and ˆDSS as
the method requires. The method is direct with neither
a model matching nor cost function minimization.
The cost of acquiring information by natural selection
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
More Related Content
Similar to shrinkage-parameters-for-each-explanatory-variable-found-via-particle-swarm-optimization-in-ridge-regression-peertechz-journal-of-computer-science-and-engineering-peertechz-journals
Trends in Computer Science and Information Technology
This document summarizes a research article about using particle swarm optimization to find different shrinkage parameters (k values) for each explanatory variable in ridge regression, rather than a single k value. Ridge regression is used to address multicollinearity issues in multiple regression analysis. Typically, ridge regression estimates a single k value, but this study uses an algorithm based on particle swarm optimization to estimate different k values for each variable. The study applies this new method to real data and simulations to evaluate its performance compared to other ridge regression methods.
Particle Swarm Optimization based K-Prototype Clustering Algorithm
This document summarizes a research paper that proposes a new Particle Swarm Optimization (PSO) based K-Prototype clustering algorithm to cluster mixed numeric and categorical data. It begins with background information on clustering algorithms like K-Means, K-Modes, and K-Prototype. It then describes the K-Prototype algorithm, PSO, and discrete binary PSO. Related work integrating PSO with other clustering algorithms is also reviewed. The proposed approach uses binary PSO to select improved initial prototypes for K-Prototype clustering in order to obtain better clustering results than traditional K-Prototype and avoid local optima.
I017235662
This document discusses using particle swarm optimization to improve the k-prototype clustering algorithm. The k-prototype algorithm clusters data with both numeric and categorical attributes but can get stuck in local optima. The proposed method uses particle swarm optimization, a global optimization technique, to guide the k-prototype algorithm towards better clusterings. Particle swarm optimization models potential solutions as particles that explore the search space. It is integrated with k-prototype clustering to avoid locally optimal solutions and produce better clusterings. The method is tested on standard benchmark datasets and shown to outperform traditional k-modes and k-prototype clustering algorithms.
Using particle swarm optimization to solve test functions problems
In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
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.
4 tracking objects of deformable shapes
The document describes a method for tracking objects of deformable shapes in images. It proposes representing the matching of a deformable template to an image as a minimum cost cyclic path in a product space of the template and image. An energy functional is introduced that consists of a data term favoring strong image gradients, a shape consistency term favoring similar tangent angles, and an elastic penalty. Optimization is performed using a minimum ratio cycle algorithm parallelized on GPUs. This provides efficient, pixel-accurate segmentation and correspondence between template and image curve. The method can be extended to 4D to segment and track multiple deformable anatomical structures in medical images.
Numerical modeling to evaluate pile head deflection under the lateral load
Abstract The complex behavior of pile head deflection under the lateral load can be studied using various analytical methods and the softwares. Often the lateral pile load testing is carried out in the field to confirm the calculated lateral pile capacity. However, even with the use of sophisticated latest softwares, the accurate deflection of pile head cannot be estimated. Hence an attempt has been made in this paper to evaluate the pile head deflection using the field load-deflection data and the corresponding soil and pile properties. A preliminary mathematical model has been developed using a technique of dimensional analysis (DA) to evaluate pile head deflection under different pile diameters, different pile materials and varying soil conditions. The estimated pile head deflection using DA equation is compared with 14nos. of measured lateral pile load test results conducted at the site. It can be observed from this study that, the dimensional analysis can be used effectively to estimate the pile head deflection. More variables based on more field results can be introduced in the mathematical model to increase the accuracy in the estimation of pile head deflection. Keywords: Pile head deflection, Lateral pile load, Dimensional analysis
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...International Journal of Science and Research (IJSR)
This paper discusses the possible applications of particle swarm optimization (PSO) in the Power system. One of the problems in Power System is Economic Load dispatch (ED). The discussion is carried out in view of the saving money, computational speed – up and expandability that can be achieved by using PSO method. The general approach of the method of this paper is that of Dynamic Programming Method coupled with PSO method. The feasibility of the proposed method is demonstrated, and it is compared with the lambda iterative method in terms of the solution quality and computation efficiency. The experimental results show that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently in ED problems.
Calculation of solar radiation by using regression methods
Abstract. In this study, solar radiation was estimated at 53 location over Turkey with
varying climatic conditions using the Linear, Ridge, Lasso, Smoother, Partial least, KNN
and Gaussian process regression methods. The data of 2002 and 2003 years were used to
obtain regression coefficients of relevant methods. The coefficients were obtained based on
the input parameters. Input parameters were month, altitude, latitude, longitude and landsurface
temperature (LST).The values for LST were obtained from the data of the National
Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer
(NOAA-AVHRR) satellite. Solar radiation was calculated using obtained coefficients in
regression methods for 2004 year. The results were compared statistically. The most
successful method was Gaussian process regression method. The most unsuccessful method
was lasso regression method. While means bias error (MBE) value of Gaussian process
regression method was 0,274 MJ/m2, root mean square error (RMSE) value of method was
calculated as 2,260 MJ/m2. The correlation coefficient of related method was calculated as
0,941. Statistical results are consistent with the literature. Used the Gaussian process
regression method is recommended for other studies.
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...Nooria Sukmaningtyas
Making full use of abundant renewable solar energy through the development of photovoltaic (PV)
technology is an effective means to solve the problems such as difficulty in electricity supply and energy
shortages in remote rural areas. In order to improve the electricity generating efficiency of PV cells, it is
necessary to track the maximum power point of PV array, which is difficult to make under partially shaded
conditions due to the odds of the appearance of two or more local maximum power points., In this paper, a
control algorithm of maximum power point tracking (MPPT) based on improved particle swarm optimization
(IPSO) algorithm is presented for PV systems. Firstly, the current in maximum power point is searched
with the IPSO algorithm, and then the real maximum power point is tracked through controlling the output
current of PV array. The MPPT method based on IPSO algorithm is established and simulated with Matlab
/ Simulink, and meanwhile, the comparison between IPSO MPPT algorithm and traditional MPPT algorithm
is also performed in this paper. It is proved through simulation and experimental results that the IPSO
algorithm has good performances and very fast response even to partial shaded PV modules, , which
ensures the stability of PV system.Ds33717725
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Ds33717725
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Ap33243246
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Ap33243246
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
A Combined Entropy-FR Weightage Formulation Model for Delineation of Groundwa...
This document presents a study that develops a combined entropy-frequency ratio (FR) weightage formulation model to delineate groundwater potential zones. Digital elevation models and satellite imagery are used to prepare thematic maps of factors like slope and rainfall. These maps are divided into classes and their pixel counts are calculated to determine area percentages. Frequency ratios are then calculated comparing area percentages of each class to the total area. Entropy and information coefficients are also calculated. Finally, weights are assigned to each class for each thematic map by combining the entropy and FR values using the proposed entropy-FR model. This provides objective weights to replace subjective weights. The weighted thematic maps are then overlaid to produce a composite groundwater potential zones map. The
3 article azojete vol 7 24 33
This document discusses using a particle swarm optimization algorithm to solve the K-node set reliability optimization problem for distributed computing systems. The K-node set reliability optimization problem aims to maximize the reliability of a subset of k nodes in a distributed computing system while satisfying a specified capacity constraint. It presents the problem formulation and describes particle swarm optimization, a metaheuristic optimization technique inspired by swarm intelligence. The proposed algorithm applies a discrete particle swarm optimization approach to solve the K-node set reliability optimization problem, which is demonstrated on an example distributed computing system topology.
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...CrimsonPublishersRDMS
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Study on the Uniqueness of Inverse Solutions by Fabian Pöhl* in Crimson Publishers: Peer Reviewed Material Science JournalsThe inverse scattering series for tasks associated with primaries: direct non...
The inverse scattering series for tasks associated with primaries: direct non-linear inversion of 1D elastic media. In this paper, research on direct inversion for two pa-
rameter acoustic media (Zhang and Weglein, 2005) is
extended to the three parameter elastic case. We present
the first set of direct non-linear inversion equations for
1D elastic media (i.e., depth varying P-velocity, shear
velocity and density). The terms for moving mislocated
reflectors are shown to be separable from amplitude
correction terms. Although in principle this direct
inversion approach requires all four components of elastic
data, synthetic tests indicate that consistent value-added
results may be achieved given only ˆDPP measurements.
We can reasonably infer that further value would derive
from actually measuring ˆDPP , ˆD PS, ˆDSP and ˆDSS as
the method requires. The method is direct with neither
a model matching nor cost function minimization.
Similar to shrinkage-parameters-for-each-explanatory-variable-found-via-particle-swarm-optimization-in-ridge-regression-peertechz-journal-of-computer-science-and-engineering-peertechz-journals (20)
Trends in Computer Science and Information Technology
Trends in Computer Science and Information Technology
Particle Swarm Optimization based K-Prototype Clustering Algorithm
Particle Swarm Optimization based K-Prototype Clustering Algorithm
Using particle swarm optimization to solve test functions problems
Using particle swarm optimization to solve test functions problems
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...
Modified Multiphase Level Set Image Segmentation Search for Energy Formulatio...
Numerical modeling to evaluate pile head deflection under the lateral load
Numerical modeling to evaluate pile head deflection under the lateral load
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...
A Case Study of Economic Load Dispatch for a Thermal Power Plant using Partic...
Calculation of solar radiation by using regression methods
Calculation of solar radiation by using regression methods
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Opti...
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...
MPPT for Photovoltaic System Using Multi-objective Improved Particle Swarm Op...
A Combined Entropy-FR Weightage Formulation Model for Delineation of Groundwa...
A Combined Entropy-FR Weightage Formulation Model for Delineation of Groundwa...
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...
Measuring Plastic Properties from Sharp Nanoindentation: A Finite-Element Stu...
The inverse scattering series for tasks associated with primaries: direct non...
The inverse scattering series for tasks associated with primaries: direct non...
Recently uploaded
The cost of acquiring information by natural selection
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
Direct Seeded Rice - Climate Smart Agriculture
Direct Seeded Rice - Climate Smart AgricultureInternational Food Policy Research Institute- South Asia Office
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Farming systems analysis: what have we learnt?.pptx
Presentation given at the official farewell of Prof Ken Gillet at Wageningen on 13 June 2024
在线办理(salfor毕业证书)索尔福德大学毕业证毕业完成信一模一样
学校原件一模一样【微信：741003700 】《(salfor毕业证书)索尔福德大学毕业证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
8.Isolation of pure cultures and preservation of cultures.pdf
Isolation of pure culture, its various method.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
The binding of cosmological structures by massless topological defects
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Gadgets for management of stored product pests_Dr.UPR.pdf
Insectsplayamajorroleinthedeteriorationoffoodgrainscausingbothquantitativeandqualitativelosses
Wellprovedthatnogranariescanbefilledwithgrainswithoutinsectsastheharvestedproducecontainegg(or)larvae(or)pupae(or)adultinsectinthembecauseoffieldcarryoverinfestationwhichcannotbeavoidedindevelopingcountrieslikeIndia
Simpletechnologiesfortimelydetectionofinsectsinthestoredproduceandtherebyplantimelycontrolmeasures
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
学校原件一模一样【微信：741003700 】《(UAM毕业证书)马德里自治大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Recently uploaded (20)
The cost of acquiring information by natural selection
The cost of acquiring information by natural selection
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
waterlessdyeingtechnolgyusing carbon dioxide chemicalspdf
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
aziz sancar nobel prize winner: from mardin to nobel
aziz sancar nobel prize winner: from mardin to nobel
Farming systems analysis: what have we learnt?.pptx
Farming systems analysis: what have we learnt?.pptx
Basics of crystallography, crystal systems, classes and different forms
Basics of crystallography, crystal systems, classes and different forms
8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
shrinkage-parameters-for-each-explanatory-variable-found-via-particle-swarm-optimization-in-ridge-regression-peertechz-journal-of-computer-science-and-engineering-peertechz-journals
- 1. Peertechz Journal of Computer Science and Engineering Peertechz Journals
- 2. RESEARCH ARTICLE Shrinkage Parameters for Each Explanatory Variable Found Via Particle Swarm Optimization in Ridge Regression Eren Bas*, Erol Egrioglu and Vedide Rezan Uslu *Corresponding author: Eren Bas, Giresun University, Faculty of Arts and Science, Department of Statistics, Gure Campus, Giresun, Turkey, Tel: +90 454 3101400; Fax: +90 454 3101477 Dates: Received: 23 February, 2017; Accepted: 11 March, 2017; Published: 13 March, 2017 Citation: Bas E, Egrioglu E, Uslu VR (2017) Shrinkage Parameters for Each Explanatory Variable Found Via Particle Swarm Optimization in Ridge Regression. Peertechz J Comput Sci Eng 2(1): 012-020.
- 3. Abstract Ridge regression method is an improved method when the assumptions of independence of the explanatory variables cannot be achieved, which is also called multicollinearity problem, in regression analysis. One of the way to eliminate the multicollinearity problem is to ignore the unbiased property of . Ridge regression estimates the regression coeffi cients biased in order to decrease the variance of the regression coeffi cients. One of the most important problems in ridge regression is to decide what the shrinkage parameter (k) value will be. This k value was found to be a single value in almost all these studies in the literature. In this study, different from those studies, we found different k values corresponding to each diagonal elements of variance-covariance matrix of instead of a single value of k by using a new algorithm based on particle swarm optimization. To evaluate the performance of our proposed method, the proposed method is fi rstly applied to real-life data sets and compared with some other studies suggested in the ridge regression literature. Finally, two different simulation studies are performed and the performance of the proposed method with different conditions is evaluated by considering other studies suggested in the ridge regression literature..
- 4. Thank you For more information Read Online Article… https://www.peertechz.com/articles/shrinkage-parameters-for- each-explanatory-variable-found-via-particle-swarm-optimization-in- ridge-regression.pdf For Full Article PDF