Title :
Fuzzy classifications using fuzzy inference networks
Author :
Yaling Cai, Lynn ; Keung Kwan, Hon
Author_Institution :
Ginston Res. Centre, Varian Associates Inc., Palo Alto, CA, USA
fDate :
6/1/1998 12:00:00 AM
Abstract :
In this paper, fuzzy inference models for pattern classifications have been developed and fuzzy inference networks based on these models are proposed. Most of the existing fuzzy rule-based systems have difficulties in deriving inference rules and membership functions directly from training data. Rules and membership functions are obtained from experts. Some approaches use backpropagation (BP) type learning algorithms to learn the parameters of membership functions from training data. However, BP algorithms take a long time to converge and they require an advanced setting of the number of inference rules. The work to determine the number of inference rules demands lots of experiences from the designer. In this paper, self-organizing learning algorithms are proposed for the fuzzy inference networks. In the proposed learning algorithms, the number of inference rules and the membership functions in the inference rules will be automatically determined during the training procedure. The learning speed is fast. The proposed fuzzy inference network (FIN) classifiers possess both the structure and the learning ability of neural networks, and the fuzzy classification ability of fuzzy algorithms. Simulation results on fuzzy classification of two-dimensional data are presented and compared with those of the fuzzy ARTMAP. The proposed fuzzy inference networks perform better than the fuzzy ARTMAP and need less training samples
Keywords :
backpropagation; fuzzy neural nets; inference mechanisms; pattern classification; pattern recognition; self-organising feature maps; backpropagation type learning algorithms; fuzzy ARTMAP; fuzzy classifications; fuzzy inference networks; fuzzy rule-based systems; membership functions; pattern classifications; self-organizing learning algorithms; simulation results; training data; Backpropagation algorithms; Classification algorithms; Fuzzy neural networks; Fuzzy systems; Inference algorithms; Neural networks; Partitioning algorithms; Pattern classification; Pattern recognition; Training data;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.678627