Hybrid Real-Value-Genetic-Algorithm and Extended-Nelder- Mead Algorithm for Short Term Energy Demand Prediction

Hybrid Real-Value-Genetic-Algorithm and Extended-Nelder- Mead Algorithm for Short Term Energy Demand Prediction

Energy consumption planning of an area is very important. It is essential to accurately predict the amount of short-term power required by an area using a highly effective prediction technique. The real-value-genetics-algorithm (RVGA) is the most effective technique that is currently used. However,...

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Bibliographic Details
Main Authors: Wahab Musa, Ku Ruhana Ku-Mahamud, Sardi Salim, Agung Sediyono
Format: Article
Language:English
Published: UUM Press 2024-01-01
Series:Journal of ICT
Subjects:
Short term power planning
energy demand prediction
convergence speed
prediction accuracy
exploration and exploitation
Online Access:https://e-journal.uum.edu.my/index.php/jict/article/view/20064

Internet

https://e-journal.uum.edu.my/index.php/jict/article/view/20064

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