Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network
The traditional dimission prediction method for knowledge workers does not take into account the impact of job burnout on employees’ dimission tendency, resulting in low accuracy of dimission prediction. In view of the above problems, this paper introduces the employee burnout evaluation and researc...
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my.ums.eprints.336092022-08-02T02:07:37Z https://eprints.ums.edu.my/id/eprint/33609/ Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network Jiang, Mengmeng Jakaria Dasan Li, Xiaoxiao HF5548.7-5548.85 Industrial psychology The traditional dimission prediction method for knowledge workers does not take into account the impact of job burnout on employees’ dimission tendency, resulting in low accuracy of dimission prediction. In view of the above problems, this paper introduces the employee burnout evaluation and researches the knowledge employee burnout evaluation and turnover tendency prediction method based on BP neural network. After analyzing the influencing factors of job burnout of knowledge workers, the evaluation index system of job burnout is established. The weight of the job burnout evaluation index was determined by fuzzy hierarchy, and BP neural network model was established. Boosting method added the fusion layer of the correlation analysis of job burnout and turnover intention to the neural network model to predict the turnover intention of employees. In the method test, the accuracy rate of employee turnover tendency prediction is higher than 90%, the reliability of employee burnout evaluation is higher, and it is more helpful for human resource management. Hindawi 2022 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/33609/2/Research%20on%20job%20burnout%20evaluation%20and%20turnover%20tendency%20prediction%20of%20knowledge%20workers%20based%20on%20BP%20neural%20network.pdf text en https://eprints.ums.edu.my/id/eprint/33609/3/Research%20on%20job%20burnout%20evaluation%20and%20turnover%20tendency%20prediction%20of%20knowledge%20workers%20based%20on%20BP%20neural%20network.pdf Jiang, Mengmeng and Jakaria Dasan and Li, Xiaoxiao (2022) Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network. Security and Communication Networks, 2022. pp. 1-6. ISSN 1939-0114 (P-ISSN) , 1939-0122 (E-ISSN) https://www.hindawi.com/journals/scn/2022/6370886/ https://doi.org/10.1155/2022/6370886 |
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HF5548.7-5548.85 Industrial psychology Jiang, Mengmeng Jakaria Dasan Li, Xiaoxiao Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
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The traditional dimission prediction method for knowledge workers does not take into account the impact of job burnout on employees’ dimission tendency, resulting in low accuracy of dimission prediction. In view of the above problems, this paper introduces the employee burnout evaluation and researches the knowledge employee burnout evaluation and turnover tendency prediction method based on BP neural network. After analyzing the influencing factors of job burnout of knowledge workers, the evaluation index system of job burnout is established. The weight of the job burnout evaluation index was determined by fuzzy hierarchy, and BP neural network model was established. Boosting method added the fusion layer of the correlation analysis of job burnout and turnover intention to the neural network model to predict the turnover intention of employees. In the method test, the accuracy rate of employee turnover tendency prediction is higher than 90%, the reliability of employee burnout evaluation is higher, and it is more helpful for human resource management. |
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Article |
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Jiang, Mengmeng Jakaria Dasan Li, Xiaoxiao |
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Jiang, Mengmeng Jakaria Dasan Li, Xiaoxiao |
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Jiang, Mengmeng |
title |
Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
title_short |
Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
title_full |
Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
title_fullStr |
Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
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Research on job burnout evaluation and turnover tendency prediction of knowledge workers based on BP neural network |
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research on job burnout evaluation and turnover tendency prediction of knowledge workers based on bp neural network |
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Hindawi |
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2022 |
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https://eprints.ums.edu.my/id/eprint/33609/2/Research%20on%20job%20burnout%20evaluation%20and%20turnover%20tendency%20prediction%20of%20knowledge%20workers%20based%20on%20BP%20neural%20network.pdf https://eprints.ums.edu.my/id/eprint/33609/3/Research%20on%20job%20burnout%20evaluation%20and%20turnover%20tendency%20prediction%20of%20knowledge%20workers%20based%20on%20BP%20neural%20network.pdf https://eprints.ums.edu.my/id/eprint/33609/ https://www.hindawi.com/journals/scn/2022/6370886/ https://doi.org/10.1155/2022/6370886 |
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