Performance Evaluation of Laboratory Management System Based on BP Neural Network - Anjie Su; Zhigang Wu; Yifeng Yin (Discrete Dynamics in Nature and Society)
Due to the lack of scientific performance evaluation methods and effective performance management, many tax authorities’ performance evaluation and performance management are not perfect. The BP neural network has strong nonlinear mapping, self-learning, and self-adaptive abilities. It has been widely used in the field of numerical prediction and pattern recognition. Based on the exploration of neural network, this paper combines BP neural network with performance evaluation and applies BP neural network to the performance evaluation of university laboratories. Data envelopment analysis (DEA) is mainly used to evaluate the performance of other fields. This paper selects key laboratories as the research object. The performance evaluation of university laboratories based on BP neural network is studied. The existing laboratory evaluation system is scientifically and reasonably revised, reasonable scientific methods are introduced, and a complete and scientific evaluation scheme suitable for the current evaluation requirements is explored. This paper perfects the evaluation method system, so as to scientifically and reasonably allocate research resources, which can maximize the enthusiasm of research departments.