sis 24(3):

Research Article

Research on Employee Performance Management Method Based on Big Data Improvement GWO-DELM Algorithms

Download238 downloads
  • @ARTICLE{10.4108/eetsis.4916,
        author={Zhuyu Wang and Yue  Liu},
        title={Research on Employee Performance Management Method Based on Big Data Improvement GWO-DELM Algorithms},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={11},
        number={3},
        publisher={EAI},
        journal_a={SIS},
        year={2024},
        month={2},
        keywords={human resource performance management evaluation, deep extreme learning machine, grey wolf optimisation algorithm, Levy flight strategy},
        doi={10.4108/eetsis.4916}
    }
    
  • Zhuyu Wang
    Yue Liu
    Year: 2024
    Research on Employee Performance Management Method Based on Big Data Improvement GWO-DELM Algorithms
    SIS
    EAI
    DOI: 10.4108/eetsis.4916
Zhuyu Wang1, Yue Liu2,*
  • 1: Hainan Vocational University of Science and Technology, Haikou 571127, Hainan, China
  • 2: Wenzhou Polytechnic
*Contact email: 2021000034@wzpt.edu.cn

Abstract

INTRODUCTION: Accurate and objective human resources performance management evaluation methods are conducive to a comprehensive understanding of the real and objective situation of teachers, and are conducive to identifying the management, teaching and academic level of teachers, which enables teacher managers to have a clear understanding of the gaps and problems among teachers. OBJECTIVES: Aiming at the current human resources performance management evaluation method, there are evaluation indexes exist objectivity is not strong, poor precision, single method and other problems. METHODS: This research puts forward an intelligent optimisation algorithm based on the improvement of the depth of the limit of the learning machine network of human resources performance management evaluation method. (1) Through the analysis of the problems existing in the current human resources performance management, select the human resources performance management evaluation indexes, and construct the human resources performance management evaluation system; (2) Through the multi-strategy grey wolf optimization algorithm method to improve the deep learning network, and construct the evaluation model of the human resources performance management in colleges; (3) The analysis of simulation experiments verifies the high precision and real-time nature of the proposed method. RESULTS: The results show that the proposed method improves the precision of the evaluation model, improves the prediction time. CONCLUSION: This research solves the problems of low precision and non-objective system indicators of human resource performance management evaluation.