模糊评价系统中隶属函数构造与修正
CONSTRUCTION AND AMENDMENT OF SUBORDINATE FUNCTIONS IN FUZZY EVALUATION SYSTEM
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摘要: 本文系统地提出了在模糊评价中构造隶属函数时,应根据各评价因素的特征,选择不同的构造方法,本文采用了统计类比法、待定系数法和多元隶属函数法三种不同方法来构造隶属函数,同时提出了隶属函数修正及其神经网络自学习模型,并将上述思想成功地运用到了具体的评价系统中。Abstract: In this paper, the statistic and analogy method, wait coefficient method and multi-element evaluation are used in constructing the subordinate-degree functions. The self-learning medel in neural networks isput forword. The use of the above idea has been proved to be successful.
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