改进可变模糊算法在水资源承载力评价中的应用
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摘要
针对可变模糊算法在评价指标体系构建时没有考虑指标间的相关性对评价结果造成的影响,以及该算法在水资源承载力评价时没有对研究区域水资源承载力的时序变化特征进行探讨,引入了主分量分析(PCA)法以筛选出彼此间相关系数较低的指标来构建评价指标体系。因此对可变模糊算法进行了改进,旨在分析不同年份下的样本水资源承载状况的时序变化特征;同时,以大同市为例,对该地区(2010～2017年)的水资源承载状况进行评估。评估结果表明:改进后的算法与改进前的相比,在维持评价等级不变的前提下,级别特征值的稳定范围明显缩小,减少了误差范围,提高了评价等级精度。该改进算法进一步拓展和丰富了可变模糊集理论,可为后续评定其他区域的水资源承载状况提供一定的参考。
In variable fuzzy algorithm,the evaluation index system is constructed without consideration on influence of the correlation among indexes on the evaluation results and without analysis on the time series variation characteristics of the water resources carrying capacity in the evaluation. To overcome the shortcoming,Principal Component Analysis( PCA) was introduced to select the indexes with low correlation coefficient to construct the evaluation index system. The variable fuzzy algorithm was improved to analyze the time-series variation characteristics of the water resources carrying status in different years. Taking Datong City,Shanxi Province as an example,this paper evaluates the water resources carrying capacity of the city from 2010 to 2017.The evaluation results show that compared with the original algorithm,the stability range of the grade characteristic value calculated by improved algorithm is obviously reduced if under the same evaluation grade and the range of error is reduced and the accuracy of the evaluation grade is improved. The improved algorithm further expands and enriches the variable fuzzy set theory,which has some reference significance for evaluating the water resources carrying status in other regions by the variable fuzzy algorithm.
In variable fuzzy algorithm,the evaluation index system is constructed without consideration on influence of the correlation among indexes on the evaluation results and without analysis on the time series variation characteristics of the water resources carrying capacity in the evaluation. To overcome the shortcoming,Principal Component Analysis( PCA) was introduced to select the indexes with low correlation coefficient to construct the evaluation index system. The variable fuzzy algorithm was improved to analyze the time-series variation characteristics of the water resources carrying status in different years. Taking Datong City,Shanxi Province as an example,this paper evaluates the water resources carrying capacity of the city from 2010 to 2017.The evaluation results show that compared with the original algorithm,the stability range of the grade characteristic value calculated by improved algorithm is obviously reduced if under the same evaluation grade and the range of error is reduced and the accuracy of the evaluation grade is improved. The improved algorithm further expands and enriches the variable fuzzy set theory,which has some reference significance for evaluating the water resources carrying status in other regions by the variable fuzzy algorithm.
引文
[1]韩晓军.可变模糊集理论在水资源系统中的应用研究[D].大连:大连理工大学,2008.
[2]陈守煜.可变集及水资源系统优选决策可变集原理与方法[J].水利学报,2012,43(9):1066-1074.
[3]陈守煜,胡吉敏.可变模糊评价法及在水资源承载能力评价中的应用[J].水利学报,2006,37(3):264-277.
[4]薛联青,时佳,陈新芳,等.基于系统熵值分析的水资源复合系统承载力可变模糊综合研究[J].中国农村水利水电,2017(10):1-5.
[5]史毅超,唐德善,孟令爽,等.基于改进可变模糊方法的区域水资源承载力预警模型[J].水电能源科学,2018,36(1):36-39.
[6]王壬.区域水资源可持续利用评价指标体系构建和评价方法研究[D].福州:福建师范大学,2015.
[7]吕平毓,吕睿.基于改进PCA的重庆市水资源可持续利用评价[J].人民长江,2016,47(24):40-45.
[8]陈守煜.可变集—可变模糊集的发展及其在水资源系统中的应用[J].数学的实践与认识,2012,42(1):92-101.
[9]孟丽红,陈亚宁,徐祥明,等.基于可变模糊评价法的塔里木河流域水资源承载力研究[J].水土保持通报,2012,32(2):162-167.
[10]李高伟,韩美,刘莉,等.基于主成分分析的郑州市水资源承载力评价[J].地域研究与开发,2012,42(1):92-101.
[11]梅长林,周家良.实用统计方法[M].北京:科学出版社,2002.
[12]冯峰,倪广恒,何宏谋.基于逆向扩散和分层赋权黄河堤防工程安全评价[J].水利学报,2014,45(9):1048-1056.
[13]时佳,薛联青,陈新芳,等.基于综合赋权法的叶尔羌河流域水资源承载力可变模糊综合评价[J].水资源与水工程学报,2017,28(5):32-36.
[14]李艳,苏维词,杨吉,等.基于熵权模糊综合模型的重庆市水环境安全评价[J].人民长江,2017,48(9):25-29.
[15]盛海峰,安贵阳,许钦,等.基于层次分析法的蓄滞洪区多目标利用研究——以浙江省嵊州市湛头滞洪区为例[J].人民长江,2017,48(9):1-5.
[16]王惠玉.大同市海河流域水污染防治规划研究[D].杭州:浙江大学,2013.
[17]胡吉敏.沿海地区水资源承载力评价研究[D].大连:大连理工大学,2008.
[18]郭亚楠,吴泽宁,高建菊.基于主成分分析的支持向量机需水预测模型及其应用[J].中国农村水利水电,2012,12(7):76-78.
[19]李睿冉.四元联系数在区域水资源承载能力评价中的应用[J].节水灌溉,2016(11):85-87.
[20]冯耀龙,韩文秀.区域水资源承载力研究[J].水科学进展,2003,14(1):109-113.
[2]陈守煜.可变集及水资源系统优选决策可变集原理与方法[J].水利学报,2012,43(9):1066-1074.
[3]陈守煜,胡吉敏.可变模糊评价法及在水资源承载能力评价中的应用[J].水利学报,2006,37(3):264-277.
[4]薛联青,时佳,陈新芳,等.基于系统熵值分析的水资源复合系统承载力可变模糊综合研究[J].中国农村水利水电,2017(10):1-5.
[5]史毅超,唐德善,孟令爽,等.基于改进可变模糊方法的区域水资源承载力预警模型[J].水电能源科学,2018,36(1):36-39.
[6]王壬.区域水资源可持续利用评价指标体系构建和评价方法研究[D].福州:福建师范大学,2015.
[7]吕平毓,吕睿.基于改进PCA的重庆市水资源可持续利用评价[J].人民长江,2016,47(24):40-45.
[8]陈守煜.可变集—可变模糊集的发展及其在水资源系统中的应用[J].数学的实践与认识,2012,42(1):92-101.
[9]孟丽红,陈亚宁,徐祥明,等.基于可变模糊评价法的塔里木河流域水资源承载力研究[J].水土保持通报,2012,32(2):162-167.
[10]李高伟,韩美,刘莉,等.基于主成分分析的郑州市水资源承载力评价[J].地域研究与开发,2012,42(1):92-101.
[11]梅长林,周家良.实用统计方法[M].北京:科学出版社,2002.
[12]冯峰,倪广恒,何宏谋.基于逆向扩散和分层赋权黄河堤防工程安全评价[J].水利学报,2014,45(9):1048-1056.
[13]时佳,薛联青,陈新芳,等.基于综合赋权法的叶尔羌河流域水资源承载力可变模糊综合评价[J].水资源与水工程学报,2017,28(5):32-36.
[14]李艳,苏维词,杨吉,等.基于熵权模糊综合模型的重庆市水环境安全评价[J].人民长江,2017,48(9):25-29.
[15]盛海峰,安贵阳,许钦,等.基于层次分析法的蓄滞洪区多目标利用研究——以浙江省嵊州市湛头滞洪区为例[J].人民长江,2017,48(9):1-5.
[16]王惠玉.大同市海河流域水污染防治规划研究[D].杭州:浙江大学,2013.
[17]胡吉敏.沿海地区水资源承载力评价研究[D].大连:大连理工大学,2008.
[18]郭亚楠,吴泽宁,高建菊.基于主成分分析的支持向量机需水预测模型及其应用[J].中国农村水利水电,2012,12(7):76-78.
[19]李睿冉.四元联系数在区域水资源承载能力评价中的应用[J].节水灌溉,2016(11):85-87.
[20]冯耀龙,韩文秀.区域水资源承载力研究[J].水科学进展,2003,14(1):109-113.