流域生态环境质量评价的熵模糊模式识别模型

流域生态环境质量评价是协调流域生态环境的压力、状态、响应诸因子，实现流域可持续发展的一项重要调控措施，其难点是如何合理确定各评价指标的权重，以及如何有效处理评价过程中的模糊性和随机性。为此提出了最大信息熵原理与模糊模式识别方法、遗传算法相耦合的流域生态环境质量评价新模型（EFPREQEB）。在巢湖流域中的应用结果表明：用EFPREQEB进行流域生态环境质量评价，物理概念明确，计算结果客观、合理，方法简明、通用，在区域资源和环境综合评价中具有一定的应用价值。

Information Entropy Based Fuzzy Pattern Recognition Model for Basin Eco-environmental Quality Evaluation

Basin eco-environmental quality evaluation is an important adjust and control measure for coordinating pressure, state and response factors of basin eco-environmental system, and achieving basin sustainable development. The difficulty is how to determine weights of evaluation indexes with reason, and how to effectively deal with fuzziness and randomness existing in the evaluation process. For this reason, a fuzzy pattern recognition model based on maximum information entropy principle and genetic algorithm was proposed, which formed a new model, named EFPR-EQEB for short. The applied result of Chaohu basin shows that as a method for basin eco-environmental quality evaluation with distinct concept of mathematics and physics, EFPR-EQEB is concise and general. Its computation result is objective and reasonable, so it can be widely applied in different resources and environment comprehension evaluation.