面向欠发达地区大数据产业发展能力分析的网络化方法研究
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摘要
针对传统产业发展能力评价方法依赖决策者的主观判断,缺乏客观性等问题,提出应用BP神经网络模型进行大数据产业发展能力评价,设计基于熵权的BP神经网络评价模型。建立欠发达地区大数据产业发展能力评价指标体系,以贵州省产业发展数据作为实验样本,采用熵权法确定BP网络期望输出,并与BP网络实际输出进行比较。实验结果表明,所提熵权-BP评价模型优化了单一BP神经网络求权重可能带来的较大误差,提高评价准确性与客观性,适用于欠发达地区大数据产业发展能力评价。
Traditional evaluation methods of industrial development ability were mostly lack of objectivity. An evaluation model was proposed by using a BP neural network based on entropy weight. Evaluation index system of big data industry development ability in underdeveloped areas was established. Taking Guizhou industrial development data as samples, entropy weight method was used to determine expected output and compared with the actual output.The experimental results show that the proposed entropy weight-BP evaluation model can optimize error of using single BP network and improve the accuracy and objectivity of evaluation.
Traditional evaluation methods of industrial development ability were mostly lack of objectivity. An evaluation model was proposed by using a BP neural network based on entropy weight. Evaluation index system of big data industry development ability in underdeveloped areas was established. Taking Guizhou industrial development data as samples, entropy weight method was used to determine expected output and compared with the actual output.The experimental results show that the proposed entropy weight-BP evaluation model can optimize error of using single BP network and improve the accuracy and objectivity of evaluation.
引文
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[3]赵黎明,刘猛.基于熵权TOPSIS的区域科技创新能力评价模型及实证研究[J].天津大学学报(社会科学版),2014(5):385-390.ZHAO L M,LIU M.Evaluation and empirical study on regional technology innovation ability based on TOPSIS method[J].Journal of Tianjin University(Social Science Edition),2014(5):385-390.
[4]赵正.建筑业企业技术创新能力评价研究[D].郑州:河南理工大学,2011.ZHAO Z.Research on technological innovation capability of construction enterprises evaluation[D].Zhengzhou:Henan Polytechnic University,2011.
[5]FU X H.Evaluation and trend analysis on the competitiveness of information industry in six provinces:based on factor analysis of panel data[J].Journal of Xichang College,2016.
[6]LI X Z,GAO Y L,ZHAO H L.Comparative research on the IOT industry competitiveness of eastern,central and western China—a comprehensive evaluation based on TOPSIS and GRA[C]//IEEE International Conference on Grey Systems and Intelligent Services.2015:187-193.
[7]LI X G,LU J,WANG H,et al.Evaluation of application level of internet of things for coal mine[J].Industry&Mine Automation,2015.
[8]HONG Y R.The study of smart city evaluation based on the ANP-TOPSIS method[J].Journal of Industrial Technological Economics,2014.
[9]ZHENG Y,CHEN Y.Research on evaluation model of university teachers'teaching quality based on BP neural network[J].Journal of Chongqing University of Technology,2015.
[10]汪忠,袁丹,江资斌,等.基于BP神经网络的社会企业动态能力评价研究[J].中国地质大学学报(社会科学版),2016(1):153-161.WANG Z,YUAN D,JIANG Z B,et al.Evaluation of dynamic ability based on BP neural network in the social enterprise[J].Journal of China University of Geosciences(Social Sciences Edition),2016(1):153-161.
[11]邹凯,包明林.基于灰色关联理论和BP神经网络的智慧城市发展潜力评价[J].科技进步与对策,2015(17):123-128.ZOU K,BAO M L.Evaluation of smart city develop potential based on gray relation theory and BP neural network[J].Science&Technology Progress and Policy,2015(17):123-128.
[12]吴志军,王璐,史荣.基于改进BP神经网络的ATM系统信息安全评估方法[J].通信学报,2011,32(2):150-158.WU Z J,WANG L,SHI R.Approach of information security assessment for ATM system based on improved BP model of artificial neural network[J].Journal on Communications,2011,32(2):150-158.
[13]石书彪,陈焕新,李冠男,等.基于改进BP网络的冷水机组故障诊断[J].制冷学报,2015,36(6):34-39.SHI S B,CHEN H X,LI G N.Research on fault diagnosis of chillers based on improved BP network[J].Journal of Refrigeration,2015,36(6):34-39.
[14]郭俊华,程聪慧,何军,等.基于熵权法的科技人才项目绩效评价研究--以上海市“浦江人才”计划为例[J].科技进步与对策,2015(19):119-125.GUO J H,CHENG C H,HE J,et al.Research on performance evaluation for talents project based on entropy weight method-a case study on“Pujiang talents project”in Shanghai municipal[J].Science&Technology Progress and Policy,2015(19):119-125.
[15]吴冲,万翔宇.基于改进熵权法的区间直觉模糊TOPSIS方法[J].运筹与管理,2014(5):42-47.WU C,WAN X Y.Extended TOPSIS with interval-valued intuitionistic fuzzy information based on advanced entropy-weighted method[J].Operations Research and Management Science,2014(5):42-47.