Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine
This study aims to propose an efficient evaluation model for Sino foreign cooperative education projects, which can offer a reasonable reference for universities to deepen reform and innovation of education and further enhance the level of international education. The core engine of the model is the...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9042274/ |
| _version_ | 1818616962042822656 |
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| author | Wei Zhu Chao Ma Xuehua Zhao Mingjing Wang Ali Asghar Heidari Huiling Chen Chengye Li |
| author_facet | Wei Zhu Chao Ma Xuehua Zhao Mingjing Wang Ali Asghar Heidari Huiling Chen Chengye Li |
| author_sort | Wei Zhu |
| collection | DOAJ |
| description | This study aims to propose an efficient evaluation model for Sino foreign cooperative education projects, which can offer a reasonable reference for universities to deepen reform and innovation of education and further enhance the level of international education. The core engine of the model is the kernel extreme learning machine (KELM) model integrated with orthogonal learning (OL) strategy optimization. The introduction of the OL mechanism is to further strengthen the optimization capabilities of the basic SCA, which is devoted to promoting the KELM model to select the optimal parameter combination and feature subset and further enhance the KELM evaluation capability of Sino foreign cooperative education projects. To examine the performance of the proposed method, OLSCA is evaluated on 23 benchmark problems, comparison with eight other well-known methods. The experimental results have shown that the proposed OLSCA is prominently superior to existing methods on most functional problems. Meantime, OLSCA-KELM is compared against other machine learning approaches in dealing with the evaluation of education projects of Sino foreign cooperation. The simulation results illustrate that the presented OLSCA-KELM obtains better performance of classification and higher stability on all four indicators. Therefore, it is evident that the presented OLSCA-KELM can be an effective solution for the evaluation of Sino foreign cooperative education projects. |
| first_indexed | 2024-12-16T16:58:08Z |
| format | Article |
| id | doaj.art-a019b4d29978421b9283dfb89ed20bcd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T16:58:08Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-a019b4d29978421b9283dfb89ed20bcd2022-12-21T22:23:50ZengIEEEIEEE Access2169-35362020-01-018611076112310.1109/ACCESS.2020.29819689042274Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning MachineWei Zhu0Chao Ma1Xuehua Zhao2https://orcid.org/0000-0002-0003-285XMingjing Wang3https://orcid.org/0000-0003-1985-4076Ali Asghar Heidari4https://orcid.org/0000-0001-6938-9948Huiling Chen5https://orcid.org/0000-0002-7714-9693Chengye Li6School of Resources and Safety Engineering, Central South University, Changsha, ChinaSchool of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, ChinaSchool of Digital Media, Shenzhen Institute of Information Technology, Shenzhen, ChinaInstitute of Research and Development, Duy Tan University, Da Nang, VietnamSchool of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, IranCollege of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, ChinaDepartment of Pulmonary and Critical Care Medicine, The First Affiliated Hospital, Wenzhou Medical University, Wenzhou, ChinaThis study aims to propose an efficient evaluation model for Sino foreign cooperative education projects, which can offer a reasonable reference for universities to deepen reform and innovation of education and further enhance the level of international education. The core engine of the model is the kernel extreme learning machine (KELM) model integrated with orthogonal learning (OL) strategy optimization. The introduction of the OL mechanism is to further strengthen the optimization capabilities of the basic SCA, which is devoted to promoting the KELM model to select the optimal parameter combination and feature subset and further enhance the KELM evaluation capability of Sino foreign cooperative education projects. To examine the performance of the proposed method, OLSCA is evaluated on 23 benchmark problems, comparison with eight other well-known methods. The experimental results have shown that the proposed OLSCA is prominently superior to existing methods on most functional problems. Meantime, OLSCA-KELM is compared against other machine learning approaches in dealing with the evaluation of education projects of Sino foreign cooperation. The simulation results illustrate that the presented OLSCA-KELM obtains better performance of classification and higher stability on all four indicators. Therefore, it is evident that the presented OLSCA-KELM can be an effective solution for the evaluation of Sino foreign cooperative education projects.https://ieeexplore.ieee.org/document/9042274/Sine cosine algorithmswarm intelligencesino foreign cooperative education projectKernel extreme learning machineparameter optimization |
| spellingShingle | Wei Zhu Chao Ma Xuehua Zhao Mingjing Wang Ali Asghar Heidari Huiling Chen Chengye Li Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine IEEE Access Sine cosine algorithm swarm intelligence sino foreign cooperative education project Kernel extreme learning machine parameter optimization |
| title | Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine |
| title_full | Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine |
| title_fullStr | Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine |
| title_full_unstemmed | Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine |
| title_short | Evaluation of Sino Foreign Cooperative Education Project Using Orthogonal Sine Cosine Optimized Kernel Extreme Learning Machine |
| title_sort | evaluation of sino foreign cooperative education project using orthogonal sine cosine optimized kernel extreme learning machine |
| topic | Sine cosine algorithm swarm intelligence sino foreign cooperative education project Kernel extreme learning machine parameter optimization |
| url | https://ieeexplore.ieee.org/document/9042274/ |
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