Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model
Students’ performance is an important factor for the evaluation of teaching quality in colleges. The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). To the best of our k...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/1845571 |
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| author | Huan Xu |
| author_facet | Huan Xu |
| author_sort | Huan Xu |
| collection | DOAJ |
| description | Students’ performance is an important factor for the evaluation of teaching quality in colleges. The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). To the best of our knowledge, few research studies have been developed to predict students’ performance based on student behavior, and the novelty of this study is to develop a new hybrid intelligent approach in this field. According to the obtained results, the IDA-SVR model clearly outperformed the other models by achieving less mean square error (MSE). In other words, IDA-SVR with an MSE of 0.0089 has higher performance than DT with an MSE of 0.0326, SVR with an MSE of 0.0251, ANN with an MSE of 0.0241, and PSO-SVR with an MSE of 0.0117. To investigate the efficacy of IDA, other parameter optimization methods, that is, the direct determination method, grid search method, GA, FA, and PSO, are used for a comparative study. The results show that the IDA algorithm can effectively avoid the local optima and the blindness search and can definitely improve the speed of convergence to the optimal solution. |
| format | Article |
| id | doaj-art-e391a8db98724f408da9147820e7dc6b |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-e391a8db98724f408da9147820e7dc6b2025-08-20T03:26:31ZengWileyComplexity1099-05262022-01-01202210.1155/2022/1845571Prediction of Students’ Performance Based on the Hybrid IDA-SVR ModelHuan Xu0Department of Public TeachingStudents’ performance is an important factor for the evaluation of teaching quality in colleges. The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). To the best of our knowledge, few research studies have been developed to predict students’ performance based on student behavior, and the novelty of this study is to develop a new hybrid intelligent approach in this field. According to the obtained results, the IDA-SVR model clearly outperformed the other models by achieving less mean square error (MSE). In other words, IDA-SVR with an MSE of 0.0089 has higher performance than DT with an MSE of 0.0326, SVR with an MSE of 0.0251, ANN with an MSE of 0.0241, and PSO-SVR with an MSE of 0.0117. To investigate the efficacy of IDA, other parameter optimization methods, that is, the direct determination method, grid search method, GA, FA, and PSO, are used for a comparative study. The results show that the IDA algorithm can effectively avoid the local optima and the blindness search and can definitely improve the speed of convergence to the optimal solution.http://dx.doi.org/10.1155/2022/1845571 |
| spellingShingle | Huan Xu Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model Complexity |
| title | Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model |
| title_full | Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model |
| title_fullStr | Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model |
| title_full_unstemmed | Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model |
| title_short | Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model |
| title_sort | prediction of students performance based on the hybrid ida svr model |
| url | http://dx.doi.org/10.1155/2022/1845571 |
| work_keys_str_mv | AT huanxu predictionofstudentsperformancebasedonthehybrididasvrmodel |