Intelligent Evaluation of Innovative Enterprise Performance - Construction of BPNN Model based on Improved WOA Optimization

Abstract

With the economic progress, the environment in which enterprises operation is becoming increasingly complex. Intelligent performance evaluation of innovative enterprises is of great significance for their own development. The traditional performance evaluation indicators of enterprises rely too much on their financial indicators, leading producers and operators to pay more attention to the short-term financial performance growth of the enterprise. The long-term development of enterprises is neglected, resulting in weak core competitiveness. Therefore, to better achieve the scientific evaluation of innovative enterprise performance, based on the innovative enterprise performance evaluation index system, an innovative enterprise performance intelligent evaluation model with the whale optimization algorithm optimized backpropagation neural network is constructed. For the shortcomings of the whale optimization algorithm in the operation, the wolf swarm algorithm isintroduced to optimize it. The experimental results show that the evaluation model based on the improved whale optimization backpropagation neural network proposed in the study has very small errors in the evaluation results of different samples, with no more than 3%. This indicates that the performance evaluation index system for innovative enterprises can objectively reflect enterprise performance. This evaluation model can offer a reasonable analysis of enterprise performance, providing reference for intelligent evaluation of innovative enterprise performance.