Adaptive fuzzy inference neural network
نویسندگان
چکیده
An adaptive fuzzy inference neural network (AFINN) is proposed in this paper. It has self-construction ability, parameter estimation ability and rule extraction ability. The structure of AFINN is formed by the following four phases: (1) initial rule creation, (2) selection of important input elements, (3) identification of the network structure and (4) parameter estimation using LMS (least-mean square) algorithm. When the number of input dimension is large, the conventional fuzzy systems often cannot handle the task correctly because the degree of each rule becomes too small. AFINN solves such a problem by modification of the learning and inference algorithm. 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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ورودعنوان ژورنال:
- Pattern Recognition
دوره 37 شماره
صفحات -
تاریخ انتشار 2004