Rule-Based Fuzzy-Neural Networks Using the Identification Algorithm of the GA Hybrid Scheme |
Park, Ho-Sung
(Department of Control & Instrumentation Engineering, Wonkwang University)
Oh, Sung-Kwun (School of Electrical Electronic & Information Engineering, Wonkwang University) |
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Fuzzy sets
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Outline of a new approach to the analysis of complex systems and decision processes
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DOI |
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Parallel Problem Solving from Nature 2, Manner
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Identification of fuzzy systems by means of an auto-tuning algorithm and its application to nonlinear systems
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DOI ScienceOn |
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On the principles of fuzzy neural networks
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DOI ScienceOn |
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Prediction of Gas Turbine NOx Emissions using Polynomial Neural Network
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Fuzzy nenral networks: A survey
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DOI ScienceOn |
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A new approach to fuzzy-neural modeling
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DOI ScienceOn |
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Identification of fuzzy models with the aid of evolutionary data granulation
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The design of optimal fuzzy-neural networks structure by means of ga and an aggregate weighted performance index
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Hybrid identification of fuzzy rule-based models
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DOI ScienceOn |
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Computational Intelligence by Programming focused on Fuzzy
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A simply identified Sugeno-type fuzzy model via double clustering
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DOI |
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Emission Pattern Model for the Atmosphere Pollution Material of a Power Plant
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Fuzzy-neural networks based on improved fuzzy input space and its optimization
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