Author(s)

Lei Pang, Qiying Wang

Corresponding Author

Qiying Wang

ABSTRACT

This paper designs a five-dimensional scientific and technological enterprise core competitiveness evaluation index system from the perspective of science and technology enterprises from the perspective of academic circles on the core competitiveness evaluation system of science and technology enterprises. At the same time, the system evaluation method based on neural network is proposed. Through the simulation experiment and the ability of self-learning, self-adaptation and self-organization, the BP neural network model based on artificial intelligence is constructed to systematically analyze the core competitiveness of science and technology enterprises and establish close proximity. With the combination of qualitative and quantitative evaluation models of leadership thinking, the simulation experiment is used to calculate the weights, remove the subjectivity and uncertainty of the model, and reveal the true core competitiveness level of real technology enterprises. Empirical studies show that the index system and the neural network expert system can better solve the problem of evaluating the core competitiveness of enterprises.

KEYWORDS

BP neural network, core competence, system learning, influencing factors