摘要
城市人居环境是评价城市居民生活质量和满意度的重要指标.为实现肇庆市人居环境的合理评价,提出一套契合肇庆市经济发展状况和资源环境背景的人居环境评价指标体系.针对评价指标维度过多,采用主成分分析方法对肇庆市人居环境指标体系进行降维处理.为提高人居环境评价精度,针对SVR模型的预测精度受参数组合C、ε和g的值的选择影响,提出一种基于ABC-SVR的人居环境评价方法.研究结果表明,ABC-SVR可以有效提高人居环境评价精度,为人居环境评价提供了新的方法和途径,从而为肇庆人居环境建设提供决策依据,对把肇庆建成可持续发展的宜居城市具有很强的理论和现实意义.
Urban human settlements environment is an important index to evaluate the quality of life and satisfaction of urban residents.In order to realize the reasonable evaluation of Zhaoqing's human settlements environment,a set of evaluation index system of human settlements environment is put forward,which is in line with the economic development situation and the background of resources and environment of Zhaoqing.In view of the excessive dimension of evaluation index,the principal component analysis method is used to reduce the dimension of Zhaoqing's human settlements environment index system.In order to improve the accuracy of human settlements environment assessment,a human settlements environment assessment method based on ABC-SVR was proposed,in which the prediction accuracy of SVR model was affected by the selection of parameters combination C,ε and g.The results show that ABC-SVR can effectively improve the accuracy of human settlements environment assessment,and provide a new method and approach for human settlements environment assessment,thus providing decision-making basis for the construction of human settlements environment in Zhaoqing,which has a strong theoretical and practical significance for building Zhaoqing into a sustainable and livable city.
作者
纪广月
JI Guangyue(Guangdong University of Business and Technology,Zhaoqing 526020,China)
出处
《应用泛函分析学报》
2020年第3期182-192,共11页
Acta Analysis Functionalis Applicata
基金
广东省教育厅高校特色创新类项目(自然科学)(2017GKTSCX109)。
关键词
人居环境
人工蜂群算法
支持向量回归
主成分分析
数据降维
human settlements environment
artificial bee colony algorithm
support vector regression
principal component analysis
data dimensionality reduction
