Research on human resource management performance evaluation based on BP algorithm

With economic globalisation and in the face of increasingly fierce market competition, enterprises must establish an evaluation mechanism that can promote the company’s development and motivate employees to improve performance in order to achieve the company’s strategic goals. In view of the characteristics and problems of enterprise performance appraisal, a performance evaluation method based on artificial neural network (ANN) technology is proposed. This study uses BP algorithm to comprehensively evaluate the performance of enterprises and construct an evaluation network. According to the statistics of 75 power companies in the province from 2018 to 2021, the training was carried out in batches, and the 10-fold cross-validation method was used to find the smallest optimisation value of the error term (average overall relative error) of the test set. The training set is set as 70% and the test set as 30%, and the termination condition is used to end the training process when the training error is <0.0001. This proves that the use of BP neural network for performance evaluation can effectively avoid the influence of subjective factors on the evaluation results, so as to establish a more objective comprehensive evaluation system.