An improved arithmetic optimization algorithm for training feedforward neural networks under dynamic environments

This paper proposes an improved Arithmetic Optimization Algorithm (AOA) to train artificial neural networks (ANNs) under dynamic environments. Despite many successful applications of metaheuristic training of ANNs, these studies assume static environments, which might not be realistic in real-world...

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Veröffentlicht in:	Knowledge-based systems Jg. 263; S. 110274
Hauptverfasser:	Gölcük, İlker, Ozsoydan, Fehmi Burcin, Durmaz, Esra Duygu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 05.03.2023
Schlagworte:	Arithmetic optimization algorithm Artificial neural networks Concept drift Dynamic optimization Arithmetic optimization algorithm Concept drift Artificial neural networks Dynamic optimization
ISSN:	0950-7051, 1872-7409
Online-Zugang:	Volltext
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