A hierarchical procedure for the synthesis of ANFIS networks
type: Item
instance of: scholarly article
title: A hierarchical procedure for the synthesis of ANFIS networks
zbMATH Open document ID: 1270.68248
DOI: 10.1155/2012/491237
author: Massimo Panella
published in: Advances in Fuzzy Systems
publication date: 2013-08-27T00:00:00Z
review text: Summary: Adaptive neurofuzzy inference systems (ANFIS) represent an efficient technique for the solution of function approximation problems. When numerical samples are available in this regard, the synthesis of ANFIS networks can be carried out exploiting clustering algorithms. Starting from a hyperplane clustering synthesis in the joint input-output space, a computationally efficient optimization of ANFIS networks is proposed in this paper. It is based on a hierarchical constructive procedure, by which the number of rules is progressively increased and the optimal one is automatically determined on the basis of learning theory in order to maximize the generalization capability of the resulting ANFIS network. Extensive computer simulations prove the validity of the proposed algorithm and show a favorable comparison with other well-established techniques.
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 65D15
zbMATH DE Number: 6202091
Wikidata QID: Q58698122
describes a project that uses: ANFIS
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/491237
OpenAlex ID: W2144141835
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description: scientific article; zbMATH DE number 6202091