Fuzzy Swarm Net (FSN) for Classification in Data Mining

Fuzzy Swarm Net (FSN) for Classification in Data Mining

Bijan Bihari Misra, Satchidananda Dehuri, Ganapati Panda, Pradipta Kishore Dash


In this paper, we have used a fuzzy net trained by the particle swarm optimization (PSO) technique for classification task of data mining. Fuzzy net uses a single layer neural network to reduce the complexities associated with multi-layer perceptron (MLP). In addition, we trained the network by using PSO to obtain optimal weight vectors, which reduces the problem of being trapped into a local minimum. From the simulation study, it is observed that the fuzzy swarm net (FSN) gives a promising result. Further, we compared the result obtained from FSN with multi-layer perceptron (MLP) radial basis function (RBF). The results obtained from FSN draws a clear edge between FSN and RBF and a competitive result with MLP.


Fuzzy Net, Multi-layer Perceptron, Particle Swarm Optimization, Classification, Data Mining, Radial Basis Neural Network