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选取的隶属函数使神经网络权值有一定的知识表示意义，并通过模糊化层将输入特征量转化为模糊量。
The selected membership function made neural network weight values have definite knowledge meaning, and the input characteristic variables were translated into fuzzy variables by fuzzy layer.
针对一般的模糊综合评判法在权重确定方面具有一定的随意性，提出了一种基于熵权的模糊综合评判方法。
In this paper, a method of fuzzy comprehensive evaluation based on entropy weight is presented because ordinary fuzzy comprehensive evaluation has defect in the aspect of determining weight.
模糊性词语的运用提高了语言表达的灵活性，给执法者留下一定得自由裁量权，增强了法律法规的适用性。
The use of fuzzy words improved language expression of flexibility, give law enforcers leave must discretion, strengthened the laws and regulations of applicability.
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