Self-Learning and Adaptive Algorithms for Business Applications
A Guide to Adaptive Neuro-Fuzzy Systems for Fuzzy Clustering Under Uncertainty Conditions
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- Description
- Contents
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- About
Introduction 1. Review of the Problem Area 2. Adaptive Methods of Fuzzy Clustering 3. Kohonen Maps and their Ensembles for Fuzzy Clustering Tasks 4. Simulation Results and Solutions for Practical Tasks Conclusion
This guide explains how to apply methods using systems built by a combination of the neural network approach and fuzzy logic (neuro-fuzzy systems) to solve practical data classification problems in business. It describes methods aimed at handling the main types of uncertainties in data, using adaptive methods of fuzzy clustering; the use of Kohonen maps and their ensembles for fuzzy clustering tasks; and simulation results of these neuro-fuzzy architectures, their learning methods, self-organization, and clustering procedures.