Research on Evaluation of University Scientific Research Team Based on SOM Neural Network

Abstract

The comprehensive strength of university research teams is an important indicator to evaluate the academic research level and innovation ability of colleges and universities, and it also has an important impact on the competitiveness of Chinese universities in the international arena. At present, the existing methods of evaluation of university research teams at home and abroad tend to focus on the existing achievements of university research teams, while ignoring the academic competitiveness that affects the development and progress of university research teams and the environment that affects academic competitiveness. For the university research team, this paper proposes a comprehensive evaluation system that includes academic competitiveness such as academic influence, industry-university research ability, team growth ability, and subject integration ability, as well as academic environment such as team leadership, member structure, member competition, and incentives. Combined with the excellent learning and classification ability of SOM (Self-organizing Maps) neural network, this paper establishes an impact evaluation model of university scientific research team based on SOM neural network.