A Hierarchical Procedure for the Synthesis of ANFIS Networks. (4th October 2012)

• Record Type: Journal Article
• Authors: Panella, Massimo
• Other Names: Honda Katsuhiro Academic Editor.
• Is Part Of: Advances in fuzzy systems. Volume 2012(2012)
• Publication Date: 2012-10-04
• Subjects: Fuzzy systems -- Periodicals; Systèmes flous; Fuzzy systems; Periodicals; 511.313
• DOI: 10.1155/2012/491237
• Languages: English
• ISSNs: 1687-7101

Abstract

Abstract : 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.