A multi hidden recurrent neural network with a modified grey wolf optimizer
Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are needed to imitate this mechanism. A hybrid s...
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| Veröffentlicht in: | PloS one 2019-03, Vol.14 (3), p.e0213237 |
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| creator | Rashid, Tarik A Abbas, Dosti K Turel, Yalin K |
| description | Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are needed to imitate this mechanism. A hybrid system (a modified Recurrent Neural Network with an adapted Grey Wolf Optimizer) is used to forecast students' outcomes. This proposed system would improve instruction by the faculty and enhance the students' learning experiences. The results show that a modified recurrent neural network with an adapted Grey Wolf Optimizer has the best accuracy when compared with other models. |
| doi_str_mv | 10.1371/journal.pone.0213237 |
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The results show that a modified recurrent neural network with an adapted Grey Wolf Optimizer has the best accuracy when compared with other models.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0213237</identifier><identifier>PMID: 30917155</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Analysis ; Area Under Curve ; Artificial intelligence ; Artificial neural networks ; Biology and Life Sciences ; College students ; Colleges & universities ; Comparative analysis ; Computer and Information Sciences ; Decision making ; Early warning systems ; Engineering and Technology ; Humans ; Hybrid systems ; Logistic Models ; Model accuracy ; Neural networks ; Neural Networks, Computer ; Physical Sciences ; Problems ; Recurrent neural networks ; Research and Analysis Methods ; ROC Curve ; Students</subject><ispartof>PloS one, 2019-03, Vol.14 (3), p.e0213237</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Rashid et al. 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| subjects | Algorithms Analysis Area Under Curve Artificial intelligence Artificial neural networks Biology and Life Sciences College students Colleges & universities Comparative analysis Computer and Information Sciences Decision making Early warning systems Engineering and Technology Humans Hybrid systems Logistic Models Model accuracy Neural networks Neural Networks, Computer Physical Sciences Problems Recurrent neural networks Research and Analysis Methods ROC Curve Students |
| title | A multi hidden recurrent neural network with a modified grey wolf optimizer |
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