基于Hopfield神经网络的企业创新能力评价
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摘要
企业创新能力评价是一个非线性、多因素的复杂过程,传统评价方法存在主观性等缺陷,难以对企业创新能力做出客观评价,导致评价准确率较低。文中基于企业创新能力的主要影响因素,构建了客观的评价指标,提出了离散Hopfield神经网络模型,并利用神经元具有学习记忆的训练功能,通过仿真技术手段完成准确的动态评价。
Enterprise Innovation Capability is a complex process with non-linear and multi-factors. The traditional evaluation methods have such defects as subjectivity and it is difficult to make an objective comment,and the result is low accuracy. Based on the main influencing factors of enterprise's innovation ability,this paper constructs an objective evaluation index,discrete Hopfield Neural Network model,the model utilizes the training function of neurons to learn and memorize,and completes an accurate dynamic evaluation with simulation techniques.
Enterprise Innovation Capability is a complex process with non-linear and multi-factors. The traditional evaluation methods have such defects as subjectivity and it is difficult to make an objective comment,and the result is low accuracy. Based on the main influencing factors of enterprise's innovation ability,this paper constructs an objective evaluation index,discrete Hopfield Neural Network model,the model utilizes the training function of neurons to learn and memorize,and completes an accurate dynamic evaluation with simulation techniques.
引文
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[6] Yadira Hernández-Solano,Miguel Atencia,Gonzalo Joya,Francisco Sandoval. A discrete gradient method to enhance the numerical behaviour of Hopfield networks[J].Neurocomputing,2015,164.
[7]Xin-Ge Liu,Feng-Xian Wang,Mei-Lan Tang,Sai-Bing Qiu. Stability and synchronization analysis of neural networks via Halanay-type inequality[J]. Journal of Computational and Applied Mathematics,2016.
[8]Jianjun Bai,Renquan Lu,Anke Xue,Qingshan She,Zhonghua Shi. Finite-time stability analysis of discrete-time fuzzy Hopfield neural network[J]. Neurocomputing,2015,159.
[9]Xin-Ge Liu,Feng-Xian Wang,Mei-Lan Tang,Sai-Bing Qiu. Stability and synchronization analysis of neural networks via Halanay-type inequality[J]. Journal of Computational and Applied Mathematics,2017,319.
[10]董微微,蔡玉胜.我国国家自主创新示范区创新能力评价[J].工业技术经济,2018,37(08):78-85.
[11]黄鲁成,陈笑,杨早立.北京高新技术企业创新能力研究[J].中国科技论坛,2019(01):89-99.
[2] HU Dawei. Introduction to Influence Factors and Countermeasures of Coal Enterprise Cost[J]. Economic Vision,2013,20(5):934-937.
[3]A. Gnanavelbabu,P. Arunagiri. Ranking of MUDA using AHP and Fuzzy AHP algorithm[J]. Materials Today:Proceedings,2018,5(5):77-91.
[4]Xin-Ge Liu,Feng-Xian Wang,Mei-Lan Tang,Sai-Bing Qiu. Stability and synchronization analysis of neural networks via Halanay-type inequality[J]. Journal of Computational and Applied Mathematics,2017,319.
[5]Yongkun Li,Li Yang. Almost automorphic solution for neutral type high-order Hopfield neural networks with delays in leakage terms on time scales[J]. Applied Mathematics and Computation,2014,242.
[6] Yadira Hernández-Solano,Miguel Atencia,Gonzalo Joya,Francisco Sandoval. A discrete gradient method to enhance the numerical behaviour of Hopfield networks[J].Neurocomputing,2015,164.
[7]Xin-Ge Liu,Feng-Xian Wang,Mei-Lan Tang,Sai-Bing Qiu. Stability and synchronization analysis of neural networks via Halanay-type inequality[J]. Journal of Computational and Applied Mathematics,2016.
[8]Jianjun Bai,Renquan Lu,Anke Xue,Qingshan She,Zhonghua Shi. Finite-time stability analysis of discrete-time fuzzy Hopfield neural network[J]. Neurocomputing,2015,159.
[9]Xin-Ge Liu,Feng-Xian Wang,Mei-Lan Tang,Sai-Bing Qiu. Stability and synchronization analysis of neural networks via Halanay-type inequality[J]. Journal of Computational and Applied Mathematics,2017,319.
[10]董微微,蔡玉胜.我国国家自主创新示范区创新能力评价[J].工业技术经济,2018,37(08):78-85.
[11]黄鲁成,陈笑,杨早立.北京高新技术企业创新能力研究[J].中国科技论坛,2019(01):89-99.