2026 Vol.9 Feb.N01   

• Title: A Method for Evaluating the Efficiency of Technology Transfer in Higher Education Institutions Using a Backpropagation Neural Ne
• Name: Qinghua Fan,Jian Shen
• Company: Jilin Communications Polytechnic, Changchun 130012, China
• Abstract:

   Most quantitative methods for evaluating the efficiency of technology transfer in universities rely on either a single subjective or objective weighting approach. Since a single weighting method struggles to achieve a balanced distribution of subjective and objective weights, it results in poor evaluation accuracy and fails to comprehensively reflect the efficiency of technology transfer in universities. To address this, we propose a method for evaluating the efficiency of technology transfer in universities using a BP neural network.First- and second-level indicators are determined from the "organization-process-outcome" perspective, and indicators are screened using a combination of expert scoring and the membership analysis method.Using game theory, subjective and objective weights are linearly combined. The objective function is defined as the sum of the relative entropy of the combined weights and the relative entropies of the subjective and objective weights. By minimizing the relative entropy, the combined weights are made to approximate the subjective and objective weights. The Lagrange multiplier method is then employed to solve for the equilibrium solution, thereby obtaining reasonable combined weights.The equilibrium information from both subjective and objective weights is embedded into a BP network structure. Through nonlinear mapping operations, a comprehensive score is output, and combined with grading criteria, this enables a quantitative evaluation of efficiency. In the experiment, the accuracy of the proposed method was tested. The test comparison results clearly demonstrate that when the proposed method is used to evaluate the efficiency of technology transfer in higher education institutions, the mean confidence level of the efficiency score is 0.85, indicating a relatively ideal evaluation outcome.

  
  

• Keyword: BP neural network; universities; scientific and technological achievements; transformation efficiency; evaluation method;
• DOI: 10.12250/jpciams2026090214
• Citation form: 名字.题目[J]. Computer Informatization and Mechanical System,2026,Vol.9,pp.

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