基于离散Hopfield神经网络的高校科研能力评价研究

Wei Dai, Zhangming Shi
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引用次数: 1

摘要

本文介绍了一种基于改进离散Hopfield神经网络的高校科研能力评价模型,可为高校识别自身科研能力状况、提升科研能力、提升排名提供科学参考。该模型将科研指标的评价概念转化为定量数据,作为Hopfield神经网络的输入,以综合评价结果作为输出。利用Matlab进行实证分析发现,利用该模型对高校科研能力进行评价,既能克服评价对象在评价过程中出现的主观因素造成的混乱,又能得到满意的评价结果,具有广泛的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Evaluation of University Scientific Research Capability Based on Discrete Hopfield Neural Network
This paper introduces an evaluation model for the university scientific research capability based on improved discrete Hopfield neural network ,which can provides scientific reference for colleges and universities to identify the status of their own research capability, enhance scientific research capability and improve their ranks. The model makes concepts of evaluation for scientific research indexes into quantitative data and use them as a Hopfield neural network input, use comprehensive evaluation results as output. Using Matlab to make an empirical analysis we found that if use this model to evaluate university scientific research capability, it can not only overcome the disorder causing by subjective factors of evaluated subject appearing the evaluation process but also can receive a satisfactory evaluating results, with broad applicability.
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