Multi-Layer Perception model with Elastic Grey Wolf Optimization to predict student achievement

This study proposes a Grey Wolf Optimization (GWO) variant named Elastic Grey Wolf Optimization algorithm (EGWO) with shrinking, resilient surrounding, and weighted candidate mechanisms. Then, the proposed EGWO is used to optimize the weights and biases of Multi-Layer Perception (MLP), and the EGWO-...

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Veröffentlicht in:	PloS one Jg. 17; H. 12; S. e0276943
Hauptverfasser:	Song, Yinqiu, Meng, Xianqiu, Jiang, Jianhua
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 30.12.2022 Public Library of Science (PLoS)
Schlagworte:	Academic achievement Academic Success Achievement Algorithms Analysis Behavior Big Data Biology and Life Sciences Classrooms Colleges & universities Data mining Datasets Ecology and Environmental Sciences Education Educational technology Efficiency Evaluation Humans Leadership Machine learning Mathematical analysis Mathematical models Mathematical optimization Methods Model accuracy Modelling Multilayers Neural networks Optimization Optimization algorithms People and Places Perception Physical Sciences Prediction models Research and Analysis Methods Semantics Social Sciences Students Training Portugal
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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