This document discusses hierarchical forecasting and reconciliation for temporally aggregated data that exhibits seasonal patterns. It analyzes 10 years of monthly foreign tourist visitation data to Kerala, India aggregated into monthly, quarterly, half-yearly, and annual levels. Different forecasting strategies are evaluated, including bottom-up, top-down, and optimal combination approaches using exponential smoothing techniques. The mean absolute percentage error is used to compare the accuracy of forecasts from each strategy. Preliminary results suggest the bottom-up approach outperforms other strategies on average and across all levels of the data hierarchy.
Demand Forecasting, undeniably, is the single most
important component of any organizations Supply Chain. It
determines the estimated demand for the future and sets the level
of preparedness that is required on the supply side to match the
demand. It goes without saying that if an organization doesnt get
its forecasting accurate to a reasonable level, the whole supply
chain gets affected. Understandably, Over/Under forecasting has
deteriorating impact on any organizations Supply Chain and
thereby on P and L. Having ascertained the importance of De-
mand Forecasting, it is only fair to discuss about the forecasting
techniques which are used to predict the future values of demand.
The input that goes in and the modeling engine which it goes
through are equally important in generating the correct forecasts
and determining the Forecast Accuracy. Here, we present a very
unique model that not only pre-processes the input data, but
also ensembles the output of two parallel advanced forecasting
engines which uses state-of-the-art Machine Learning algorithms
and Time-Series algorithms to generate future forecasts. Our
technique uses data-driven statistical techniques to clean the data
of any potential errors or outliers and impute missing values if
any. Once the forecast is generated, it is post processed with
Seasonality and Trend corrections, if required.Since the final
forecast is the result of statistically pre-validated ensemble of
multiple models, the forecasts are stable and accuracy variation
is very minimal across periods and forecast horizons. Hence it
is better at estimating the future demand than the conventional
techniques.
Anattemptto forecast demand and buildforecasting modelsis made in the article. The modern business is conducted in the contextof fierce competition. Adequate decisions require deep, comprehensive assessment of the situation and a reliable forecast of developments. Proven methodsof forecastingby extrapolation of the previous results to the future are poorly suited for qualitative changes in theeconomy, especially in a complex, dynamic,and uncertain environment. Acompany that has managed to forecastthe situationcorrectlyearnsadditional profit in comparison with the one that abstained from forecasting. Afirm that made the wrong forecastloses the most. The simplest forecastis to extrapolate the current situation to the future. This technique may be well suited fora stable and clear situation, but it begins to fail in a dynamic and uncertain environment, as well as in the contextof structural adjustments
Demand Forecasting, undeniably, is the single most
important component of any organizations Supply Chain. It
determines the estimated demand for the future and sets the level
of preparedness that is required on the supply side to match the
demand. It goes without saying that if an organization doesnt get
its forecasting accurate to a reasonable level, the whole supply
chain gets affected. Understandably, Over/Under forecasting has
deteriorating impact on any organizations Supply Chain and
thereby on P and L. Having ascertained the importance of De-
mand Forecasting, it is only fair to discuss about the forecasting
techniques which are used to predict the future values of demand.
The input that goes in and the modeling engine which it goes
through are equally important in generating the correct forecasts
and determining the Forecast Accuracy. Here, we present a very
unique model that not only pre-processes the input data, but
also ensembles the output of two parallel advanced forecasting
engines which uses state-of-the-art Machine Learning algorithms
and Time-Series algorithms to generate future forecasts. Our
technique uses data-driven statistical techniques to clean the data
of any potential errors or outliers and impute missing values if
any. Once the forecast is generated, it is post processed with
Seasonality and Trend corrections, if required.Since the final
forecast is the result of statistically pre-validated ensemble of
multiple models, the forecasts are stable and accuracy variation
is very minimal across periods and forecast horizons. Hence it
is better at estimating the future demand than the conventional
techniques.
Anattemptto forecast demand and buildforecasting modelsis made in the article. The modern business is conducted in the contextof fierce competition. Adequate decisions require deep, comprehensive assessment of the situation and a reliable forecast of developments. Proven methodsof forecastingby extrapolation of the previous results to the future are poorly suited for qualitative changes in theeconomy, especially in a complex, dynamic,and uncertain environment. Acompany that has managed to forecastthe situationcorrectlyearnsadditional profit in comparison with the one that abstained from forecasting. Afirm that made the wrong forecastloses the most. The simplest forecastis to extrapolate the current situation to the future. This technique may be well suited fora stable and clear situation, but it begins to fail in a dynamic and uncertain environment, as well as in the contextof structural adjustments
Interventions required to meet business objectives from Forecasting Methods,
Quantitative & Qualitative Methods,
Forecast Accuracy , Error Reduction to
CPFR
Interventions required to meet business objectives - from Forecasting Methods,
Forecast Accuracy / Error Reduction,
Integrate – Sales Forecast / Production to undertaking a CPFR
Demand Forecasting of a Perishable Dairy Drink: An ARIMA ApproachIJDKP
Any organization engaged in trading aims to maximize earnings while maintaining costs at
their bare minimum. One of the inexpensive ways to accomplish this objective is through sales forecasting.
Evidence from empirical literature has shown that sales forecasting frequently results in better customer
service, fewer returns of goods, less dead stock, and effective production scheduling. Successful sales forecasting systems are essential for the food sector because of the limited shelf life of food goods and the
significance of product quality. In this paper, we generated sales of forecasts for a perishable dairy drink
using the famous ARIMA approach. We identified the ARIMA (0, 1, 1)(0, 1, 1)12 as the proper model for
modeling the daily sales forecast of the perishable drink. After performing model diagnostics, the model
satisfied all the model assumptions, and a strong positive linear relationship (R
2 > 0.9) was observed when
the actual daily sales were regressed against the forecasted values.
Performance Assessment of Agricultural Research Organisation Priority Setting...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Technological Forecasting: Methodology Embrapa Brazilian Company IJERA Editor
Structural, economic and social changes are present in organizations. One of the strategies for decision-making, which leads to organizational policies, is the construction of feasible and doable technological scenarios that enable innovations to trigger the processes of technological change. This study to analyze the prospect of technological scenarios in the Brazilian Agricultural Research Agency a public organization of Research, Development and Innovation, based on scenario building in its operating environment. For the methodological procedures, a systemic review addressing the problem of searching for qualitative bias was developed. Taking this study’s point of view, the research is exploratory and descriptive. The sources of data collection were primary and secondary. The technical consistency of prospective scenarios for the company was highlighted in the results of this study, as this was the object of this analysis. Through the collected data it was possible to verify the inferences between literature and the applied method. [JEL Classification: O310].
Interventions required to meet business objectives from Forecasting Methods,
Quantitative & Qualitative Methods,
Forecast Accuracy , Error Reduction to
CPFR
Interventions required to meet business objectives - from Forecasting Methods,
Forecast Accuracy / Error Reduction,
Integrate – Sales Forecast / Production to undertaking a CPFR
Demand Forecasting of a Perishable Dairy Drink: An ARIMA ApproachIJDKP
Any organization engaged in trading aims to maximize earnings while maintaining costs at
their bare minimum. One of the inexpensive ways to accomplish this objective is through sales forecasting.
Evidence from empirical literature has shown that sales forecasting frequently results in better customer
service, fewer returns of goods, less dead stock, and effective production scheduling. Successful sales forecasting systems are essential for the food sector because of the limited shelf life of food goods and the
significance of product quality. In this paper, we generated sales of forecasts for a perishable dairy drink
using the famous ARIMA approach. We identified the ARIMA (0, 1, 1)(0, 1, 1)12 as the proper model for
modeling the daily sales forecast of the perishable drink. After performing model diagnostics, the model
satisfied all the model assumptions, and a strong positive linear relationship (R
2 > 0.9) was observed when
the actual daily sales were regressed against the forecasted values.
Performance Assessment of Agricultural Research Organisation Priority Setting...iosrjce
IOSR Journal of Business and Management (IOSR-JBM) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of business and managemant and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications inbusiness and management. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Technological Forecasting: Methodology Embrapa Brazilian Company IJERA Editor
Structural, economic and social changes are present in organizations. One of the strategies for decision-making, which leads to organizational policies, is the construction of feasible and doable technological scenarios that enable innovations to trigger the processes of technological change. This study to analyze the prospect of technological scenarios in the Brazilian Agricultural Research Agency a public organization of Research, Development and Innovation, based on scenario building in its operating environment. For the methodological procedures, a systemic review addressing the problem of searching for qualitative bias was developed. Taking this study’s point of view, the research is exploratory and descriptive. The sources of data collection were primary and secondary. The technical consistency of prospective scenarios for the company was highlighted in the results of this study, as this was the object of this analysis. Through the collected data it was possible to verify the inferences between literature and the applied method. [JEL Classification: O310].
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.