Predicting the performance of solar dish Stirling power plant using a hybrid random vector functional link/chimp optimization model

•A solar dish/Stirling power plant was modeled using artificial intelligence models.•A hybrid random vector functional link (RVFL) models were developed.•Four meta-heuristic optimizers were used to find the optimum structure of RVFL.•A chimp optimization algorithm (CHOA) was declared as the best opt...

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Veröffentlicht in:	Solar energy Jg. 222; S. 1 - 17
Hauptverfasser:	Zayed, Mohamed E., Zhao, Jun, Li, Wenjia, Elsheikh, Ammar H., Elaziz, Mohamed Abd, Yousri, Dalia, Zhong, Shengyuan, Mingxi, Zhu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 01.07.2021 Pergamon Press Inc
Schlagworte:	Algorithms Artificial intelligence Chimp optimization algorithm Computer applications Heuristic methods Hybrid systems Optimization algorithms Optimization models Performance prediction Power plants Power production prediction Prediction models Random Vector Functional Link Soft computing Software Solar collectors Solar dish Stirling power plant Solar energy Spherical search optimization Statistical analysis Statistics Swarm intelligence Whale optimization algorithm Spherical search optimization Power production prediction Random Vector Functional Link Chimp optimization algorithm Whale optimization algorithm Solar dish Stirling power plant
ISSN:	0038-092X, 1471-1257
Online-Zugang:	Volltext
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