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机构地区:[1]长江大学信息与数学学院,湖北荆州434023
出 处:《长江大学学报(自科版)(上旬)》2015年第1期20-23,36,共5页JOURNAL OF YANGTZE UNIVERSITY (NATURAL SCIENCE EDITION) SCI & ENG
基 金:国家自然科学基金项目(60873021/F0201)
摘 要:以武汉市环境监测中心站2014年8月25日上午09∶00发布的武汉市空气质量实时监测数据为样本,使用SPSS软件的对应分析过程对原数据处理得到惯量和卡方分解等统计量信息,并通过软件绘出行点和列点的散布图。结合按距离解释和按象限解释等方法分析所得图表中的信息,分析了武汉市大气中各污染物的分类情况,并结合地区差异等因素分析得出各观测区域内主要污染物的成因。对比分析因子分析法和对应分析法的处理结果,2种方法所得结论一致,但对应分析方法所得结果更简明直观,更适于分析该类问题,可以为整治城市空气污染问题和制定相关政策法案等提供重要的参考依据。The correspondence analysis method of SPSS software was used for Original data-processing to obtain the statistics information of Inertia and chi-square decomposition based on the samples using the real-time air quality monitoring data released by Wuhan Environmental Monitoring Center Station at 9:00 am on August 25.2014.A scatter plot with row points and column points was drawn.Combined the information obtained from the chart using distance and quadrant explanation,the classification of each pollutant in the atmosphere of the municipality was analyzed.Then the causes of major pollutants in each observation area and solutions were analyzed combined with the factors of regional differences.Comparing with the results between factor analysis and correspondence analysis methods,it indicated that the results of both were consistent,but the result of correspondence analysis was more simple and intuitive,and it was more suitable for dealing with these type of problems.Correspondence analysis can be used to analyze and process the data of each monitoring center station,it provides important reference for urban air pollution remediation and the development of relevant policy.
分 类 号:O212.4[理学—概率论与数理统计]
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