检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:徐建中[1] 孙颖 孙晓光 XU Jian-zhong;SUN Ying;SUN Xiao-guang(School of Economics and Management,Harbin Engineering University,Harbin 150001,China;School of Economic and Management,Tsinghua University,Beijing 100084,China)
机构地区:[1]哈尔滨工程大学经济管理学院,黑龙江哈尔滨150001 [2]清华大学经济管理学院,北京100084
出 处:《运筹与管理》2020年第1期131-140,共10页Operations Research and Management Science
基 金:国家自然科学基金资助项目(71273072);黑龙江省自然科学基金资助项目(LH2019G014);黑龙江应用技术研究与开发计划项目(GC14D501);黑龙江省哲学社会科学资助项目(14B009)。
摘 要:为客观和准确地评价制造企业绿色创新能力,本文构建了制造企业绿色创新能力评价指标体系,提出了基于熵权TOPSIS的粒子群(PSO)优化极限学习机(ELM)集成学习算法的制造企业绿色创新能力评价模型.首先运用熵权法客观确定指标权重,结合TOPSIS测度并综合评价制造企业绿色创新能力,然后将评价值作为先验样本进行极限学习机的训练与测试,训练过程中利用PSO优化极限学习机的网络结构与连接权值,从而对绿色创新能力进行全面的分析和评价.最后以60家制造企业为例进行实证分析,并将熵权TOPSIS-PSO-ELM算法与极限学习机回归拟合算法对比,结果表明:基于熵权TOPSIS-PSO-ELM模型所得评价结果较已有方法更为准确可靠.此外,为进一步提高我国制造企业绿色创新发展能力提出了理论建议.In order to objectively and accurately evaluate the environmental innovation capability of manufacturing enterprises,this study establishes anevaluation indicator system of environmental innovation ability of manufactur-ing enterprises.We propose the evaluation model of environmental innovation capability of manufacturing enterprises based on the integrated learning algorithm which is Entropy weighted TOPSIS and Extreme Learning Machine(ELM)with Particle Swarm Optimization(PSO).First,the Entropy weight method is employed to cal-culate the weighted index and comprehensive evaluation of environmental innovation capability of manufacturing enterprises by TOPSIS method.Then,the evaluation value is used as a priori sample for the training and testing of Extreme Learning Machine.This model produces a better network architecture and initial connection weights,and trains the traditional backward propagation again by PSO.The environmental innovation ability of the manu-facturing enterprises is analyzed and evaluated in a more comprehensive way.Furthermore,an empirical evalua-tion of the sixty enterprises are taken as the example to illustrate the feasibility of this method,and a comparative analysis of the environmental innovative capability of the enterprises was also carried on.The validity of the prediction model is verified by comparing the proposed the Entropy weighted TOPSIS-PSO-ELM algorithm with traditional ELM regression fitting algorithms.The resultsshows that the evaluation results based on the Entropy weighted TOPSIS-PSO-ELM model is more accurate and reliable than the existing methods.In addition,it provides theoretical suggestions for further improving the environmental innovation capability of manufacturing enterprises in China.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.198