摘要
提出一种基于粗糙集(Rough Set,RS)—最小二乘支持向量机(Least-squares-Support Vector Machine,LS-SVM)复合的建筑物室内空气品质评价方法,选取描述室内空气品质的六项监测指标作为评价因子,利用RS理论,对室内空气品质监测数据进行属性约简,消除冗余信息,用约简后的规则集对LS-SVM进行训练,使其达到满意精度。实验仿真表明:该复合方法具有良好的收敛速度与非线性逼近能力,能对室内空气品质进行实时、准确的评价,为建筑物室内空气品质监测、环境污染治理提供科学依据。
An arithmetic for evaluation of indoor air quality was proposed based on composite of Rough Set（RS）-Least-Squares Support Vector Machine（LS-SVM）.Six monitoring indexes of indoor air quality are utilized as the evaluation items,use the RS to reduce the properties of indoor air quality monitoring data,eliminate the redundant information,and use the reductive regulations to train the LS-SVM,achieve the satisfactory precision.The simulation results indicate that the method has better performance of convergence speed and nonlinear approaching,and gives a real-time and accurate result of evaluation of indoor air quality,it provides a scientific basis for building indoor environment monitor and pollution control.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第16期235-237,241,共4页
Computer Engineering and Applications
基金
陕西省自然科学基础研究基金(No.SJ08F30)
陕西省教育厅专项科研项目(No.08JK321)~~
关键词
粗糙集
最小二乘支持向量机
室内空气品质评价
Rough Set（RS）
Least-Squares Support Vector Machine（LS-SVM）
evaluation of indoor air quality
