Job Performance Analysis Method based on Dropout Deep Neural Network
文献类型:会议论文
作者 | Ruoyi Cheng1,2,3; Jie Zhou2,3![]() |
出版日期 | 2024 |
会议名称 | IMCEC 2024 - IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference |
会议日期 | 2024 |
会议地点 | 不详 |
通讯作者邮箱 | zhouj@psych.ac.cn |
页码 | 271-275 |
英文摘要 | In this study, marriage and work domains are connected, and a moderated mediation effect model is constructed to explore the mechanism of marital satisfaction and work performance. Using the correlation and regression analysis data, this paper establishes a centralized neural network for comparison and uses the Dropout deep neural network for job performance analysis. When designing the feature extraction module, this study added a batch normalization layer between the convolution layer and the pooling layer to improve the algorithm to accelerate the network's training, stabilize the training gradient, and prevent the phenomenon of overfitting. The results show that job engagement plays a chain-mediated role in the positive relationship between marital satisfaction and job performance. |
收录类别 | EI |
会议录 | IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference
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语种 | 英语 |
源URL | [http://ir.psych.ac.cn/handle/311026/48501] ![]() |
专题 | 中国科学院心理研究所 |
作者单位 | 1.Beijing Health Vocational College, Beijing; 101101, China 2.University of Chinese Academy of Sciences, Department of Psychology, Beijing; 100049, China 3.Chinese Academy of Sciences, Institute of Psychology, Beijing; 100100, China |
推荐引用方式 GB/T 7714 | Ruoyi Cheng,Jie Zhou. Job Performance Analysis Method based on Dropout Deep Neural Network[C]. 见:IMCEC 2024 - IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference. 不详. 2024. |
入库方式: OAI收割
来源:心理研究所
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