基于最大熵原理的水环境模糊优化评价模型

POMEbased fuzzy optimal evaluation model of water environment

基于最大熵原理,应用工程模糊集理论中的相对隶属度等概念,综合考虑水环境评价的随机性和模糊性,定义了不同的加权广义权距离来表征待评价水样与水质标准的差异,建立了两个水环境相对隶属度模糊优化评价模型.我国12个有代表性的湖库营养化评价实例表明:所建模型的评价结果基本一致,与调查结果相符;对比单一考虑模糊性的模型,所建两个模型评价结果的描述要细致一些;且具有较小的Shannon熵,即此次评价的不确定性小.

Based on the Principle of Maximum Entropy (POME) and the concept of relative membership degree in the theory of fuzzy set in engineering, and in consideration of the randomness and fuzziness of water resources evaluation, the difference is defined between water quality standard and the qualities of a sample evaluated and represented with different generalized weighted distances, and two fuzzy optimal models are developed for evaluation of the relative membership degree of water environment. The eutrophication evaluation of 12 representative lakes and reservoirs in China shows that the evaluated results by the two models are in good agreement, and consistent with investigations; compared with the results from the model only considering fuzziness, the results evaluated by the present models are sophisticated, and a small Shannon entropy is included, indicating less uncertainty of the evaluated results.