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Artificial-Intelligence-Based Fuzzy Comprehensive Evaluation of Innovative Knowledge Management in Universities

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  • Rui Liu
  • Hui Zhang
  • Wen-Tsao Pan

Abstract

By considering the comprehensive impact index ranking of all factors to identify the impact of university innovation knowledge, the group decision-making characteristic root method, decision-making experiment, and evaluation laboratory method are used to analyze the factors that affect the university’s innovative knowledge management ability. The key factors affecting management capabilities have been identified and reviewed to establish measures to enhance the innovative knowledge management capabilities of colleges and universities. Using artificial intelligence-based knowledge management fuzzy evaluation algorithm evaluation model to evaluate the innovation knowledge management of 16 universities, the results obtained are consistent with the actual evaluation results of the year; this result proves the fuzziness of university innovation knowledge management, which is based on artificial intelligence fuzzy. The algorithm is evaluated. The results show that the evaluation model is feasible.

Suggested Citation

  • Rui Liu & Hui Zhang & Wen-Tsao Pan, 2022. "Artificial-Intelligence-Based Fuzzy Comprehensive Evaluation of Innovative Knowledge Management in Universities," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-11, April.
    • Handle: RePEc:hin:jnlmpe:5655269
    DOI: 10.1155/2022/5655269
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    Cited by:

    1. Fanshun Zhang & Zhuorui Zhang & Quanquan Zhang & Xiaochun Zhu, 2023. "Dynamic Evaluation of Product Innovation Knowledge Concerning the Interactive Relationship between Innovative Subjects: A Multi-Objective Optimization Approach," Mathematics, MDPI, vol. 11(9), pages 1-33, April.

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