Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model
The collaborative innovation plan for colleges and universities is one of the important plans for the construction of high-level universities in Jiangsu Province. A key aspect of this plan is the development of collaborative innovation centers in colleges and universities. Based on the second-phase...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/11/6818 |
| _version_ | 1797597788893085696 |
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| author | Daopan Zhang Sihua Wang |
| author_facet | Daopan Zhang Sihua Wang |
| author_sort | Daopan Zhang |
| collection | DOAJ |
| description | The collaborative innovation plan for colleges and universities is one of the important plans for the construction of high-level universities in Jiangsu Province. A key aspect of this plan is the development of collaborative innovation centers in colleges and universities. Based on the second-phase construction of collaborative innovation centers in 76 colleges and universities in Jiangsu Province, this paper constructs performance evaluation indicators and proposes an unsupervised factor importance analysis model based on Back Propagation Neural Network (BPNN)-dominated K-means and random forests. According to the analysis results, suggestions for further promoting the development of high-quality collaborative innovation centers in colleges and universities are provided. |
| first_indexed | 2024-03-11T03:10:24Z |
| format | Article |
| id | doaj.art-40a0d2acb94347cb8c37247dbaf1633c |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T03:10:24Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-40a0d2acb94347cb8c37247dbaf1633c2023-11-18T07:37:08ZengMDPI AGApplied Sciences2076-34172023-06-011311681810.3390/app13116818Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis ModelDaopan Zhang0Sihua Wang1College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaSchool of Safety Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaThe collaborative innovation plan for colleges and universities is one of the important plans for the construction of high-level universities in Jiangsu Province. A key aspect of this plan is the development of collaborative innovation centers in colleges and universities. Based on the second-phase construction of collaborative innovation centers in 76 colleges and universities in Jiangsu Province, this paper constructs performance evaluation indicators and proposes an unsupervised factor importance analysis model based on Back Propagation Neural Network (BPNN)-dominated K-means and random forests. According to the analysis results, suggestions for further promoting the development of high-quality collaborative innovation centers in colleges and universities are provided.https://www.mdpi.com/2076-3417/13/11/6818collaborative innovation centersk-meansBPNN networkrandom forestperformance analysis |
| spellingShingle | Daopan Zhang Sihua Wang Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model Applied Sciences collaborative innovation centers k-means BPNN network random forest performance analysis |
| title | Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model |
| title_full | Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model |
| title_fullStr | Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model |
| title_full_unstemmed | Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model |
| title_short | Performance Analysis of University Collaborative Innovation Center Based on BPNN-Dominated K-Means–Random Forest Unsupervised Factor Importance Analysis Model |
| title_sort | performance analysis of university collaborative innovation center based on bpnn dominated k means random forest unsupervised factor importance analysis model |
| topic | collaborative innovation centers k-means BPNN network random forest performance analysis |
| url | https://www.mdpi.com/2076-3417/13/11/6818 |
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