A Self-Organizing Fuzzy Neural Networks
نویسندگان
چکیده
This paper proposes a novel clustering algorithm for the structure learning of fuzzy neural networks. Our clustering algorithm uses the reward and penalty mechanism for the adaptation of the fuzzy neural networks prototypes at every training sample. Compared with the classical clustering algorithms, the new algorithm can on-line partition the input data, pointwise update the clusters, and self-organize the fuzzy neural structure.
منابع مشابه
Fuzzy Rough Granular Neural Networks for Pattern Analysis
Granular computing is a computational paradigm in which a granule represents a structure of patterns evolved by performing operations on the individual patterns. Two granular neural networks are described for performing the pattern analysis tasks like classification and clustering. The granular neural networks are designed by integrating fuzzy sets and fuzzy rough sets with artificial neural ne...
متن کاملMunicipal Creditworthiness Modelling by Neural Networks
The paper presents the design of municipal creditworthiness parameters. Further, the design of model for municipal creditworthiness classification is presented. The realized data pre-processing makes the suitable economic interpretation of results possible. Municipalities are assigned to clusters by unsupervised methods. The combination of Kohonen’s self-organizing feature maps and K-means algo...
متن کاملWater Quality Data Processing Using Fuzzy Neural Networks and Kohonen Self Organizing Maps
This paper is about different techniques for intelligent processing of data obtained with water quality monitoring distributed systems. The techniques include a set of fuzzy neural networks (FuNNs) for modelling measuring channels and Kohonen Self Organizing Maps (K-SOMs) for information classification. Elements of FuNN and K-SOM optimization in terms of architecture and training are presented ...
متن کاملSelf-Organizing Hybrid Neurofuzzy Networks
We introduce a concept of self-organizing Hybrid Neurofuzzy Networks (HNFN), a hybrid modeling architecture combining neurofuzzy (NF) and polynomial neural networks(PNN). The development of the Self-organizing HNFN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the Self-organizing HNFN results from a...
متن کاملA comparison of self-organizing neural networks for fast clustering of radar pulses
Four self-organizing neural networks are compared for automatic deinterleaving of radar pulse streams in electronic warfare systems. The neural networks are the Fuzzy Adaptive Resonance Theory, Fuzzy Min-Max Clustering, Integrated Adaptive Fuzzy Clustering, and Self-Organizing Feature Mapping. Given the need for a clustering procedure that ooers both accurate results and computational eeciency,...
متن کامل