A Short-Term Load Forecasting Algorithm Using Support Vector Regression & Artificial Neural Network

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Article Title: A Short-Term Load Forecasting Algorithm Using Support Vector Regression & Artificial Neural Network (SVR-ANN)
Publication Title: 2020 11th IEEE Control and System Graduate Research Colloquium (ICSGRC)
Publication Type: Conference

Abstract:
Load Forecasting is the science of predicting the most economical amount of electrical power to be supplied by electrical utility companies. Energy conservation is in paired with this study which is needed for our unending need of power supply given limited source of energy. An effective way on how to do it is by using an Artificial Intelligence algorithm and as per chosen, Support Vector Regression and Artificial Neural Network are the machine learning algorithm which is a good combination for forecasting, classifying, and regression. Results were verified through statistical tools: 1) Mean Absolute Error (MAE); 2) Mean Absolute Percentage Error (MAPE). Using SVR-ANN algorithm, an averaged absolute error of 175.6893MW which corresponds to 2.47% was obtained from the analysis. Load Forecasting models play a vital role in energy conservation in efforts to prevent too much power loss in the system.

Authors:
Lourd Adrian G. Abad
Shaira Micah Sarabia
Joemer M. Yuzon
Dr. Michael C. Pacis (Adviser)

Shaira Micah Sarabia

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it very good but please more expanation

paulosalelign

Where can we get demo program with samples data.

BattleBotOfficial

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