Performance evaluation of activation functions in deep residual networks for short-term load forecasting

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Performance evaluation of activation functions in deep residual networks for short-term load forecasting

Short-Term Load Forecasting (STLF) is essential for ensuring efficient and reliable power system operations, requiring accurate predictions of electricity demand. Deep Residual Networks (DRNs), with their ability to mitigate gradient vanishing and model complex nonlinear relationships in load data,...

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Bibliographic Details
Main Authors:	Liu, Junchen, Ahmad, Faisul Arif, Samsudin, Khairulmizam, Hashim, Fazirulhisyam, Ab Kadir, Mohd Zainal Abidin
Format:	Article
Language:	English
Published:	Institute of Electrical and Electronics Engineers 2025
Online Access:	http://psasir.upm.edu.my/id/eprint/118663/ http://psasir.upm.edu.my/id/eprint/118663/1/118663.pdf

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