[1]范亚琼,燕雪峰,陈海燕. 基于改进离差最大化方法的梯形灰云评估模型[J].计算机技术与发展,2016,26(04):20-24.
　FAN Ya-qiong,YAN Xue-feng,CHEN Hai-yan. A Trapezoidal Gray Cloud Evaluation Model Based on Improved Deviation Maximization Weighting Method[J].,2016,26(04):20-24.
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 基于改进离差最大化方法的梯形灰云评估模型()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年04期
页码:
20-24
栏目:
智能、算法、系统工程
出版日期:
2016-04-10

文章信息/Info

Title:
 A Trapezoidal Gray Cloud Evaluation Model Based on Improved Deviation Maximization Weighting Method
文章编号:
1673-629X（2016)04-0020-05
作者:
 范亚琼；燕雪峰；陈海燕
 南京航空航天大学 计算机科学与技术学院
Author(s):
 FAN Ya-qiong；YAN Xue-feng；CHEN Hai-yan
关键词:
 ; 梯型灰云聚类; 改进离差最大化赋权法; 大气环境质量; 灵敏度分析
Keywords:
 ; trapezoidal gray cloud clustering; improved deviation maximum weight method; atmospheric environment quality; sensitivity analysis
分类号:
TP311
文献标志码:
A
摘要:
 针对多方案多指标中离差最大化赋权法不能充分体现指标权重在不同方案中的差别，而层次分析法能够通过指标之间的两两比较获得指标之间的相对重要性，结合层次分析法的特性对离差最大化赋权法进行改进；同时，由于在某些领域实际监测数据所能提供的信息具有不完全性和不确知性，而云理论是一种处理模糊性和随机性信息的有效工具，结合具体应用场景，提出了基于梯形云模型的白化权函数，建立了基于改进离差最大化赋权法的梯形灰云聚类评价模型。应用梯形灰云聚类评估模型对福州市近十年的大气环境质量进行评价，实验表明该模型评价结果符合客观实际，通过灵敏度分析验证了此模型的可行性和实用性。梯形灰云聚类评价模型为综合评价问题提供了一种新的有效途径。
Abstract:
 Due to the problem of the deviation maximization weighting method that can’ t fully embody the difference of the weight of the index in different schemes and the characteristics of the method of the AHP that can obtain the relative importance of the index by the comparison,the AHP is introduced to improve the maximum weight of the deviation. Meanwhile,owing to the incomplete and uncertain of the amount of information provided by the monitoring data in some areas and the property of cloud theory which is an effective tool for dealing with fuzzy and random information,the whitening weight function is improved by the introduction of the trapezoid cloud model. Thus,a trapezoidal gray cloud clustering evaluation model based on the maximum weight of dispersion is established in this paper. The at-mospheric environmental quality of Fuzhou city during the last ten years is assessed by using the improved trapezoidal gray cloud cluster assessment model. Examples show that the results of the model are consistent with the objective reality. The feasibility and practicality of the model are verified by sensitivity analysis. It is the trapezoidal gray cloud clustering evaluation model that provides a new and effective way for the comprehensive evaluation.

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更新日期/Last Update: 2016-06-16