TY  - EJOU
AU  - Gu, Xianhui 
AU  - Wang, Xiaokan 
AU  - Liang, Shuang 

TI  - Employment Quality Evaluation Model Based on Hybrid Intelligent Algorithm
T2  - Computers, Materials \& Continua

PY  - 2023
VL  - 74
IS  - 1
SN  - 1546-2226

AB  - 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.
KW  - Employment quality; fuzzy c-means clustering algorithm; grey correlation analysis method; evaluation model; index system; comparative test

DO  - 10.32604/cmc.2023.028756