POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference

POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference

Fuzzy Neural Networks are hybrid systems that combine the human inference style and natural language description of fuzzy systems with the learning and parallel processing of neural networks. A novel FNN architecture, an improved selforganizing neural network algorithm and two novel fuzzy members...

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Bibliographic Details
Main Author: Ang, Kai Keng
Other Authors: Quek Hiok Chai
Format: Theses and Dissertations
Language:English
Published: 2011
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Online Access:http://hdl.handle.net/10356/42627
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Institution: Nanyang Technological University
Language: English
Description
Summary:Fuzzy Neural Networks are hybrid systems that combine the human inference style and natural language description of fuzzy systems with the learning and parallel processing of neural networks. A novel FNN architecture, an improved selforganizing neural network algorithm and two novel fuzzy membership function identification algorithms are proposed. They are the Pseudo Outer-Product based Fuzzy Neural Network using the Compositional Rule of Inference and a Singleton Fuzzifier (POPFNN-CRI(S)), the Modified Learning Vector Quantization (MLVQ) algorithm, the Fuzzy Kohonen Partition (FKP) and the Pseudo Fuzzy Kohonen Partition (PFKP) algorithms.

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