计算机技术与发展2016，Vol.26Issue(4)：20-24,30,6.DOI:10.3969/j.issn.1673-629X.2016.04.005
基于改进离差最大化方法的梯形灰云评估模型
A Trapezoidal Gray Cloud Evaluation Model Based on Improved Deviation Maximization Weighting Method
摘要
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.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Key words
trapezoidal gray cloud clustering/improved deviation maximum weight method/atmospheric environment quality/sensitivity analysis分类
信息技术与安全科学引用本文复制引用
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(4):20-24,30,6.基金项目
国防科工局“十二五”重大基础科研项目(c0420110005) （c0420110005）
