Properties of learning of a fuzzy ART variant

Georgiopoulos, Michael; Dagher, Issam; Heileman, Gregory L.; Bebis, George

doi:10.1109/icnn.1997.614209

Cited by 12 publications

(14 citation statements)

References 14 publications

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“…Blume and Esener 17 proposed an alternate approach achieving choice and matching functions at the same layer. Georgiopoulos et al 18 explained the properties of learning of a Fuzzy ART variant. Chung et al 19 applied the Fuzzy ART theory for fuzzy clustering in the input/output spaces.…”

Section: Literature Review Of Fuzzy Artmentioning

confidence: 99%

An alternative evaluation of FMEA: Fuzzy ART algorithm

Keskin

Özkan

2008

Quality & Reliability Eng

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Failure Mode and Effects Analysis (FMEA) is a technique used in the manufacturing industry to improve production quality and productivity. It is a method that evaluates possible failures in the system, design, process or service. It aims to continuously improve and decrease these kinds of failure modes. Adaptive Resonance Theory (ART) is one of the learning algorithms without consultants, which are developed for clustering problems in artificial neural networks. In the FMEA method, every failure mode in the system is analyzed according to severity, occurrence and detection. Then, risk priority number (RPN) is acquired by multiplication of these three factors and the necessary failures are improved with respect to the determined threshold value. In addition, there exist many shortcomings of the traditional FMEA method, which affect its efficiency and thus limit its realization. To respond to these difficulties, this study introduces the method named Fuzzy Adaptive Resonance Theory (Fuzzy ART), one of the ART networks, to evaluate RPN in FMEA.

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Section: Literature Review Of Fuzzy Artmentioning

confidence: 99%

An alternative evaluation of FMEA: Fuzzy ART algorithm

Keskin

Özkan

2008

Quality & Reliability Eng

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“…The subsection below provides a brief overview of the neural network model, while a detailed description of Fuzzy ART can be found in the papers of Huang, Georgiopoulos, and Heileman (1995), Georgiopoulos et al (1996Georgiopoulos et al ( , 1999, Anagnostopoulos and Georgiopouolos (2002). Additional details of the matching algorithm along with the step-by-step implementation of training are given in the Appendix of this paper.…”

Section: Fuzzy Art Neural Networkmentioning

confidence: 99%

Monitoring roundness profiles based on an unsupervised neural network algorithm

Pacella

Semeraro

2011

Computers & Industrial Engineering

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“…The step-by-step implementation [6] of the training in Fuzzy ARTMAP is presented below. The Fuzzy ARTMAP network parameters α a ,ρ a , N a , and ε are chosen, at the beginning of the training phase as follows: α a = 0.001,ρ a = 0, Na = 1, and ε = 0.000001.…”

Section: Fuzzy Artmap Training Algorithmmentioning

confidence: 99%

L-p Fuzzy ARTMAP neural network architecture

Dagher

2005

Soft Comput

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In this paper, an L-p based Fuzzy ARTMAP neural network is presented. The category choice of this network is based on the L-p norm. Geometrical properties of this architecture are presented. Comparisons between this category choice and the category choice of the Fuzzy ART-MAP are illustrated. And simulation results on the databases taken from the UCI repository are performed. It will be shown that using the L-p norm is geometrically more attractive. It will operate directly on the input patterns without the need for doing any preprocessing. It should be noted that the Fuzzy ARTMAP architecture requires two preprocessing steps: normalization and complement coding. Simulation results on different databases show the good generalization performance of the L-p Fuzzy ARTMAP compared to the performance of Fuzzy ARTMAP.

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Properties of learning of a fuzzy ART variant

Cited by 12 publications

References 14 publications

An alternative evaluation of FMEA: Fuzzy ART algorithm

An alternative evaluation of FMEA: Fuzzy ART algorithm

Monitoring roundness profiles based on an unsupervised neural network algorithm

L-p Fuzzy ARTMAP neural network architecture

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