摘要
气象服务满意度分析在公众气象服务满意度评价业务上起着非常关键的作用。针对我国31个省市的气象服务满意度现状,采用2010年全国公众气象服务评估调查数据,分别运用主成分分析法和熵值法进行分析,得到两种关于城市气象服务满意度的排序结果。但主成分分析法侧重考虑变量的相关性以及熵值法侧重考虑变量的不确定性,故将两种排序结果在通过一致性检验的基础上,运用集成综合评价法得到另外一种新的排序结果,介于以上两种结果之间。因此得到一个关于城市气象服务满意度的新认识,并给出提高气象服务满意度的建议。
Meteorological service satisfaction analysis plays a very important role in public meteorological service satisfaction evaluation.The principal component analysis and the entropy value method are used to gain two sets of ranking results about the satisfaction with the status quo of meteorological service for 31 provinces and cities in China,based on the assessment survey data of national public meteorological service in 2010.The principal component analysis emphasizes the correlation of variables,and the entropy value method emphasizes the uncertainty of variables; so the two ranking results are combined,under the prerequisite of passing the consistency test,to establish another new ranking result by using the integrated comprehensive evaluation method.A new understanding of the satisfaction of meteorological service in a city is obtained,and suggestions about improving meteorological service satisfaction are provided.
出处
《气象科技》
2014年第3期530-534,共5页
Meteorological Science and Technology
基金
公益性行业(气象)科研专项(GYHY201106037)
国家软科学(2011GXQ4B026)
气象软科学研究项目[2012]第033号资助
关键词
主成分分析
熵值法
集成综合评价法
气象服务
满意度
principal component analysis
entropy method
integrated comprehensive evaluation method
meteorological service
satisfaction