基于多判据决策的水体营养状态评价  

Assessment of nutritional status in water-body based on multi-criteria decision-making

作　　者：周晓蔚[1] 王丽萍[1] 李继清[1] 

机构地区：[1]华北电力大学可再生能源学院水资源与水利水电工程研究所,北京102206

出　　处：《生态学报》2008年第1期345-352,共8页Acta Ecologica Sinica

基　　金：国家自然科学基金资助项目(50579019);武汉大学国家重点实验室开放基金资助项目(whu2005B018)~~

摘　　要：为了准确地评价水生态系统营养状态和综合决策,通过最大熵原理耦合模糊性与随机性,建立了最大熵模糊评价模型(FAME);利用逼近理想解排序法(TOPSIS),以待决策水体样本的实测值为理想解,以评价结果中与实测值相差最大的为负理想解,建立了多判据决策模型(MCDM)。经12个湖泊实测数据验証,最大熵模糊评价与随机评价、模糊评价和灰色评价的结果较为一致,但提高了评价水体营养状态问题各层次的分辨力。多判据决策模型可解决多种方法评价结果不相容问题,使评价结果更接近水体实际情况。FAME和MCDM适用于各种水质的综合评价及决策。In order to assessment the nutritional status of the water ecosystem accurately and make integrated decision, a Fuzzy Assessment based on Maximum Entropy （FAME）is developed through the maximum entropy principle coupled with the randomness and fuzzy. Using TOPSIS （Technique for Order Preference by Similarity to Ideal Solution）, set the decision-making water bodies measure number as ideal solution, the max-difference number between the evaluation result and the measure result as the negative ideal solution, then Multiple Criteria Decision Making （MCDM） is established. According to the measured data validation of 12 lakes, the results of FAME basically consistent to the other results of the three methods （stochastic assessment method, fuzzy assessment method and grey evaluation method） is separately 83. 3% ,91.7%, 91.7%. It is concluded that all these four methods are comparable computation precision, but FAME improves the resolution of evaluation nutritional status of water body at all levels. MCDM can solve the incompatibility of evaluation indexes of water nutritional status,making the results more close to the actual situation. FAME and MCDM can be applied to the comprehensive evaluation of water quality and decision-making.

关 键 词：营养状态 评价 不确定性 最大熵原理 逼近理想解排序法 多判据决策 

分 类 号：X824[环境科学与工程—环境工程]