中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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
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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