Multi-Energy Load Prediction Method for Integrated Energy System Based on Fennec Fox Optimization Algorithm and Hybrid Kernel Extreme Learning Machine

To meet the challenges of energy sustainability, the integrated energy system (IES) has become a key component in promoting the development of innovative energy systems. Accurate and reliable multivariate load prediction is a prerequisite for IES optimal scheduling and steady running, but the uncert...

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Vydáno v:	Entropy (Basel, Switzerland) Ročník 26; číslo 8; s. 699
Hlavní autoři:	Shen, Yang, Li, Deyi, Wang, Wenbo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 17.08.2024 MDPI
Témata:	Accuracy Algorithms Alternative energy sources Analysis comprehensive weight method Cooling Correlation coefficients Energy industry Energy resources Entropy Entropy (statistics) Error analysis fennec fox optimization algorithm Forecasting hybrid kernel extreme learning machine integrated energy system Integrated energy systems Load fluctuation Machine learning Mathematical optimization Methods multi-energy load prediction Neural networks Optimization Parameter modification Predictions Renewable resources Root-mean-square errors Weighting methods comprehensive weight method hybrid kernel extreme learning machine multi-energy load prediction integrated energy system fennec fox optimization algorithm
ISSN:	1099-4300, 1099-4300
On-line přístup:	Získat plný text
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