Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education
With the promotion and development of the “Internet+,” the computer major has become a hot major in innovation and entrepreneurship education. It is more and more necessary to carry out the refined differences between majors. This is a training issue, but not an employment issue. It has become a maj...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/2425069 |
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| _version_ | 1849308122832699392 |
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| author | Jingyi Yi Xiao Cui |
| author_facet | Jingyi Yi Xiao Cui |
| author_sort | Jingyi Yi |
| collection | DOAJ |
| description | With the promotion and development of the “Internet+,” the computer major has become a hot major in innovation and entrepreneurship education. It is more and more necessary to carry out the refined differences between majors. This is a training issue, but not an employment issue. It has become a major measure for the development of international education. The international vocational training system of “three combinations and five drives” has been established and implemented. In February 2020, the State Department of Higher Education issued the key work points of the Department of Higher Education of the Ministry of Education in 2020. The document makes it clear that it must be implemented in the whole process of talent training. BP neural net model will be a brand-new research and development idea. By constructing a scientific and reasonable training assessment index system, the efficiency of computer professional technology training can be improved. Taking the development of computer specialty as the main research objective, this paper firstly establishes the evaluation index system of computer specialty for the first time, then makes a scientific evaluation of computer specialty by using BP neural net model and then carries out an empirical study of innovative employment mode through the evaluation index system and makes an empirical quantitative analysis. It is expected to be an effective basis for the social policy research of developing computer specialties. |
| format | Article |
| id | doaj-art-13faf1cfbcf84ddeb0fd965df5542eba |
| institution | Kabale University |
| issn | 1687-9619 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-13faf1cfbcf84ddeb0fd965df5542eba2025-08-20T03:54:33ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/2425069Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship EducationJingyi Yi0Xiao Cui1Shaanxi College of Communications TechnologySchool of navigationWith the promotion and development of the “Internet+,” the computer major has become a hot major in innovation and entrepreneurship education. It is more and more necessary to carry out the refined differences between majors. This is a training issue, but not an employment issue. It has become a major measure for the development of international education. The international vocational training system of “three combinations and five drives” has been established and implemented. In February 2020, the State Department of Higher Education issued the key work points of the Department of Higher Education of the Ministry of Education in 2020. The document makes it clear that it must be implemented in the whole process of talent training. BP neural net model will be a brand-new research and development idea. By constructing a scientific and reasonable training assessment index system, the efficiency of computer professional technology training can be improved. Taking the development of computer specialty as the main research objective, this paper firstly establishes the evaluation index system of computer specialty for the first time, then makes a scientific evaluation of computer specialty by using BP neural net model and then carries out an empirical study of innovative employment mode through the evaluation index system and makes an empirical quantitative analysis. It is expected to be an effective basis for the social policy research of developing computer specialties.http://dx.doi.org/10.1155/2022/2425069 |
| spellingShingle | Jingyi Yi Xiao Cui Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education Journal of Robotics |
| title | Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education |
| title_full | Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education |
| title_fullStr | Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education |
| title_full_unstemmed | Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education |
| title_short | Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education |
| title_sort | deep learning bp neural network guided evaluation of students innovation and entrepreneurship education |
| url | http://dx.doi.org/10.1155/2022/2425069 |
| work_keys_str_mv | AT jingyiyi deeplearningbpneuralnetworkguidedevaluationofstudentsinnovationandentrepreneurshipeducation AT xiaocui deeplearningbpneuralnetworkguidedevaluationofstudentsinnovationandentrepreneurshipeducation |