系统仿真学报 ›› 2019, Vol. 31 ›› Issue (1): 136-144.doi: 10.16182/j.issn1004731x.joss.18-0008

• 仿真应用工程 • 上一篇    下一篇

基于熵权-云模型的我国绿色智慧城市评价

陈莉1, 张海侠2   

  1. 1. 安徽建筑大学经管学院,安徽 合肥 230601;
    2. 江西国新咨询发展有限责任公司,江西 新余 338000
  • 收稿日期:2018-01-08 修回日期:2018-05-24 出版日期:2019-01-08 发布日期:2019-04-16
  • 作者简介:陈莉(1966-), 女, 安徽阜阳, 博士, 教授,硕导, 研究方向为技术经济理论与评价、计量经济学。
  • 基金资助:
    2017年度安徽高校人文社会科学研究重点项目(SK2017A0548),合肥市软科学研究项目(2018026),安徽省质量工程项目(2016msgzs 018),教学团队(2017jxtd029)

Evaluation of Green Smart Cities in China Based on Entropy Weight - Cloud Model

Chen li1, Zhang HaiXia2   

  1. 1. School of Management, Anhui Jianzhu University, Hefei 230601, China;
    2. Jiangxi new consulting development co. LTD, Xinyu 230601, China
  • Received:2018-01-08 Revised:2018-05-24 Online:2019-01-08 Published:2019-04-16

摘要: 对国内外绿色智慧城市的相关研究基础上,提出熵权与云模型相结合的评价方法。综合考虑主观和客观因素,对指标进行相关分析,确定评价指标集,运用云模型中的X条件云发生器得到各评价对象对应不同等级的隶属度矩阵,并与利用熵权法确定评价对象的客观权重进行模糊变换,将仿真评价结果与支持向量机的评价结果进行比较。仿真评价结果表明熵权—云模型的绿色智慧城市评价优于支持向量机,运用本方法的评价效果是合理有效的

关键词: 绿色智慧城市, 熵权法, 云模型, 支持向量机

Abstract: Based on the research on green smart city at home and abroad; and aiming at the shortcomings and deficiencies of traditional evaluation methods, this paper proposes an evaluation method of combining entropy and cloud model based on the cloud model which can realize the conversion of qualitative concept and quantitative value. This method synthetically considers the subjective and objective factors; carries on the correlation analysis to the index; determines the set of evaluation indicators; uses the X-conditional cloud generator in cloud model to obtain the different levels of membership matrix corresponding to each evaluation object; and carries on the fuzzy transformation by using the entropy weight method to determine the objective weight of the evaluation object; and after that, compares the simulation evaluation results with support vector machine evaluation results. The simulation results show that the entropy weight - cloud model is better than support vector machine in evaluating green smart cities, and the evaluation result of this method is reasonable and effective.

Key words: green smart city, entropy weight method, cloud model, support vector machine

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