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Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

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摘要 In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.
出处 《Computers, Materials & Continua》 SCIE EI 2023年第1期131-139,共9页 计算机、材料和连续体(英文)
基金 supported by the project of science and technology of Henan province under Grant No.222102240024 and 202102210269 the Key Scientific Research projects in Colleges and Universities in Henan Grant No.22A460013 and No.22B413004.
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