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熵权模糊层次分析法在林纸一体化项目环境影响评价中的应用
引用本文:俞峰,李荣钧. 熵权模糊层次分析法在林纸一体化项目环境影响评价中的应用[J]. 纸和造纸, 2012, 0(4): 43-45
作者姓名:俞峰  李荣钧
作者单位:华南理工大学工商管理学院
摘    要:通过对林纸一体化建设项目的分析,证明林纸一体化建设项目环境影响评价既涉及工业污染环境影响评价又涉及生态环境影响评价,是一项复杂的环境系统评价。为了使环境影响评价更准确可靠,提出了运用层次分析法、熵权理论与模糊综合评判相结合的评估方法。该方法由模糊数学确定各因素的隶属函数,通过层次分析法、熵权理论确定评价指标的综合权重,结合指标权重与评判矩阵进行模糊运算得到环境影响程度。通过实例证明该方法合理有效,可为决策者提供直观、可靠的依据。

关 键 词:林纸一体化项目  环境影响  模糊综合评价  层次分析法  熵权

Application of Fuzzy Analytical Hierarchy Process Based on Entropy Weight to the Environment Influence Assessment of Forestry-Paper Integration Project
YU Feng,LI Rong-jun. Application of Fuzzy Analytical Hierarchy Process Based on Entropy Weight to the Environment Influence Assessment of Forestry-Paper Integration Project[J]. Paper and Paper Making, 2012, 0(4): 43-45
Authors:YU Feng  LI Rong-jun
Affiliation:(College of Business Administration,South China University of Technology,Guangdong Guangzhou,510640 China)
Abstract:Aimed to analyze the forestry-paper integration project and pointed out that environment influence assessment for forestrypaper integration project content involves industrial pollution and ecological environmental impact assessment,which is a complex environmental system assessment.In order to make the environment influence assessment more accurate and more reliable,this paper advances a new method for evaluating the environment influence that is combined with AHP,entropy theory and fuzzy comprehensive evaluation,the concrete procedures of which are as following:first,identifying membership function of each factor by fuzzy mathematics;second,determining the comprehensive weights of evaluation factors by AHP and entropy theory,and conducting the fuzzy calculation connecting with the index weight and evaluation matrix to get the comprehensive environment influence degree;and finally,verifying that the method is rational and effective with an example.It can p rovide a reliable and convenient method for decision makers.
Keywords:forestry-paper integration project  environment influence  fuzzy comprehensive evaluation  analytical hierarchy process  entropy weight
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