基于多维正态云模型的水体富营养化评价方法
发布时间：2018-07-26 18:36
【摘要】：水体富营养化评价具有重要意义。针对评价过程中的随机性和模糊性,提出了基于多维正态云模型的水体富营养化评价方法(Multidimensional Normal Cloud Model Method, MNCM法),将各个评价因子分别作为多维正态云模型的一维属性,改进了云模型相关参数的选取,由熵权法确定评价因子的权重,生成综合所有评价因子隶属于各个营养化等级的多维正态云模型,根据确定度判定水体的营养化级别。将MNCM法应用于我国12个代表性湖库富营养化评价,并与湖库实际水质状况以及新近提出的基于一维正态云模型的水体富营养化评价方法、国内外应用较为广泛的其他常用方法(相关加权营养状态综合指数法、评分公式法、模糊综合评价法)进行对比分析。结果表明,MNCM法的评价结果与实际用水障碍情况相一致,验证了方法的可行性；MNCM法与基于一维正态云模型的水体富营养化评价方法相比,在没有增加建模复杂程度的前提下,建模过程得以简化,云模型参数选取得到改进；MNCM法与其他常用方法评价结果较为吻合,验证了方法的有效性,弥补了常用方法的局限；MNCM法根据确定度不仅可以直观判定水体营养化级别,而且可以判断处于相同级别的不同水体营养化程度的高低,更符合水体富营养化评价的复杂情况。
[Abstract]:Water eutrophication evaluation is of great significance. Aiming at the randomness and fuzziness of the evaluation process, a method of eutrophication evaluation based on multi-dimensional normal cloud model (Multidimensional Normal Cloud Model Method, MNCM) is proposed. Each evaluation factor is regarded as the one-dimensional attribute of the multi-dimensional normal cloud model. The selection of relevant parameters of cloud model is improved and the weight of evaluation factors is determined by entropy weight method. The multi-dimensional normal cloud model which synthesizes all evaluation factors is generated and the nutrient grade of water body is determined according to the degree of certainty. The MNCM method is applied to the eutrophication evaluation of 12 representative lakes and reservoirs in China. The actual water quality of the lake and reservoir and the newly proposed eutrophication evaluation method based on one-dimensional normal cloud model are proposed. Other commonly used methods at home and abroad, such as correlation weighted nutritional state comprehensive index method, scoring formula method and fuzzy comprehensive evaluation method, are compared and analyzed. The results show that the evaluation results of the MNCM method are consistent with the actual water use barriers. The feasibility of the method is verified. Compared with the water eutrophication evaluation method based on one-dimensional normal cloud model, the MNCM method does not increase the complexity of modeling. The process of modeling is simplified, and the improved MNCM method is in good agreement with other common methods, which verifies the validity of the method and makes up for the limitation of the common methods. According to the degree of determination, MNCM method can not only directly determine the water nutrition level, but also judge the level of different water bodies in the same level, which is more in line with the complex situation of eutrophication evaluation.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X824
本文编号：2146933
[Abstract]:Water eutrophication evaluation is of great significance. Aiming at the randomness and fuzziness of the evaluation process, a method of eutrophication evaluation based on multi-dimensional normal cloud model (Multidimensional Normal Cloud Model Method, MNCM) is proposed. Each evaluation factor is regarded as the one-dimensional attribute of the multi-dimensional normal cloud model. The selection of relevant parameters of cloud model is improved and the weight of evaluation factors is determined by entropy weight method. The multi-dimensional normal cloud model which synthesizes all evaluation factors is generated and the nutrient grade of water body is determined according to the degree of certainty. The MNCM method is applied to the eutrophication evaluation of 12 representative lakes and reservoirs in China. The actual water quality of the lake and reservoir and the newly proposed eutrophication evaluation method based on one-dimensional normal cloud model are proposed. Other commonly used methods at home and abroad, such as correlation weighted nutritional state comprehensive index method, scoring formula method and fuzzy comprehensive evaluation method, are compared and analyzed. The results show that the evaluation results of the MNCM method are consistent with the actual water use barriers. The feasibility of the method is verified. Compared with the water eutrophication evaluation method based on one-dimensional normal cloud model, the MNCM method does not increase the complexity of modeling. The process of modeling is simplified, and the improved MNCM method is in good agreement with other common methods, which verifies the validity of the method and makes up for the limitation of the common methods. According to the degree of determination, MNCM method can not only directly determine the water nutrition level, but also judge the level of different water bodies in the same level, which is more in line with the complex situation of eutrophication evaluation.
【学位授予单位】：南京大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X824
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相关期刊论文 前3条
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3 黄定轩;基于客观信息熵的多因素权重分配方法[J];系统工程理论方法应用;2003年04期
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