@inproceedings{82bf9a1b4afa467d918caeb9d4923db3,
title = "Self-organizing neuro-fuzzy inference system",
abstract = "The architectural design of neuro-fuzzy models is one of the major concern in many important applications. In this work we propose an extension to Rogers's ANFIS model by providing it with a selforganizing mechanism. The main purpose of this mechanism is to adapt the architecture during the training process by identifying the optimal number of premises and consequents needed to satisfy a user's performance criterion. Using both synthetic and real data, our proposal yields remarkable results compared to the classical ANFIS.",
keywords = "ANFIS, Flexible architecture, Nonlinear modeling",
author = "H{\'e}ctor Allende-Cid and Alejandro Veloz and Rodrigo Salas and Steren Chabert and H{\'e}ctor Allende",
note = "Funding Information: This work was supported by the Fondecyt 1070220 and 11060036 research grants and DGIP-UTFSM grant.; null ; Conference date: 09-09-2008 Through 12-09-2008",
year = "2008",
doi = "10.1007/978-3-540-85920-8_53",
language = "English",
isbn = "3540859195",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "429--436",
booktitle = "Progress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings",
}