Affiliations: [a] School of Business Administration, Xinjiang University of Finance and Economics, Wulumuqi, China
| [b] China Center for Internet Economy Research, Central University of Finance and Economics, Beijing, China
Correspondence:
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Corresponding author. Abuduaini Abudureheman, School of Business Administration, Xinjiang University of Finance and Economics, Wulumuqi, China. E-mail: oewitjkl8@163.com.
Abstract: Influenced by national policies and macro-economic environment, large domestic enterprises is actively promoting strategic transformation to enhance their core competitiveness, and performance evaluation of enterprises’ innovation capacity has become a hot topic in recent years. This paper proposes a performance evaluation method of enterprises’ innovation capacity based on deep learning fuzzy system model and convolutional neural network analysis of innovation network. First of all, on account of the characteristics of breakthrough innovation and drawing on the traditional innovation performance evaluation model, this paper constructs a breakthrough innovation performance evaluation index system for enterprises from the six dimensions of main resource input, technology out-turn, process management, product performance, social value and commercial Value. Secondly, the introduction of machine learning of fuzzy convolutional neural network to assess the advancement execution of enterprises is of great significance for enterprise managers to find out the problems and causes of enterprises’ innovation, optimize the allocation of enterprises’ resources and further improve the innovation performance of enterprises. The experimental results show to verify the adequacy of the algorithm.
Keywords: Innovation network, fuzzy system model, convolutional neural network (CNN)
