An Investigation of the Effects of Variable Vigilance within the RePART Neuro-Fuzzy Network
Journal of Intelligent and Robotic Systems
RePART: A Modified Fuzzy ARTMAP for Pattern Recognition
Proceedings of the 6th International Conference on Computational Intelligence, Theory and Applications: Fuzzy Days
Neuro-Fuzzy Approach to the Segmentation of Psoriasis Images
Journal of VLSI Signal Processing Systems
Fuzzy diagnosis in AHU system using dynamic fuzzy neural network
ICECS'03 Proceedings of the 2nd WSEAS International Conference on Electronics, Control and Signal Processing
A game theoretical framework on intrusion detection in heterogeneous networks
IEEE Transactions on Information Forensics and Security
An efficient adaptive fuzzy neural network (EAFNN) approach for short term load forecasting
ICAISC'10 Proceedings of the 10th international conference on Artificial intelligence and soft computing: Part I
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Navigation behaviors based on fuzzy ArtMap neural networks for intelligent autonomous vehicles
Advances in Artificial Neural Systems
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A new learning algorithm for the Simpson fuzzy min-max neural network is presented. It overcomes some undesired properties of the Simpson model. Our new algorithm improves the network performance; the classification result does not depend on the presentation order of the patterns in the training set, and at each step, the classification error in the training set cannot increase. The new neural model is particularly useful in classification problems. Tests were executed on three different classification problems: 1) with two-dimensional synthetic data; 2) with realistic data generated by a simulator to find anomalies in the cooling system of a blast furnace; and 3) with real data for industrial diagnosis. The experiments were made following some recent evaluation criteria known in the literature and by using Microsoft Visual C++ development environment on personal computers