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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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

id	sg-ntu-dr.10356-42627
record_format	dspace
spelling	sg-ntu-dr.10356-426272020-09-27T20:18:17Z POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference Ang, Kai Keng Quek Hiok Chai School of Applied Science DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence 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. Master of Philosophy (Computer Engineering) 2011-01-06T01:44:41Z 2011-01-06T01:44:41Z 1998 1998 Thesis http://hdl.handle.net/10356/42627 en 135 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle	DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Ang, Kai Keng POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
description	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.
author2	Quek Hiok Chai
author_facet	Quek Hiok Chai Ang, Kai Keng
format	Theses and Dissertations
author	Ang, Kai Keng
author_sort	Ang, Kai Keng
title	POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
title_short	POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
title_full	POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
title_fullStr	POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
title_full_unstemmed	POPFNN-CRI(S) : a fuzzy neural network based on the compositional rule of inference
title_sort	popfnn-cri(s) : a fuzzy neural network based on the compositional rule of inference
publishDate	2011
url	http://hdl.handle.net/10356/42627
_version_	1681059152631169024

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

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