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All Journal International Journal of Electrical and Computer Engineering
Anh Tuan Nguyen
Industrial University of Ho Chi Minh City
Computer Science & IT Electrical & Electronics Engineering

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Load forecasting with support vector regression: influence of data normalization on grid search algorithm Thanh Ngoc Tran; Binh Minh Lam; Anh Tuan Nguyen; Quang Binh Le
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3410-3420

Abstract

In recent years, support vector regression (SVR) models have been widely applied in short-term electricity load forecasting. A critical challenge when applying the SVR model is to determine the model for optimal hyperparameters, which can be solved using several optimization methods as the grid search algorithm. Another challenge that affects the response time and the precision of the SVR model is the normalization process of input data. In this paper, the grid search algorithm will be suggested based on data normalization methods including Z-score, min-max, max, decimal, sigmoidal, softmax; and then utilized to evaluate both the response time and precision. To verify the proposed methods, the actual electricity load demand data of two cities, including Queensland of Australia and Ho Chi Minh City of Vietnam, were utilized in this study.
Co-Authors Binh Minh Lam Quang Binh Le Thanh Ngoc Tran