TY - GEN
T1 - Self-organizing neuro-fuzzy inference system
AU - ALLENDE CID, HÉCTOR GABRIEL
AU - Veloz, Alejandro
AU - Salas, Rodrigo
AU - Chabert, Steren
AU - Allende, Héctor
N1 - Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
KW - ANFIS
KW - Flexible architecture
KW - Nonlinear modeling
UR - http://www.scopus.com/inward/record.url?scp=55349086227&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-85920-8_53
DO - 10.1007/978-3-540-85920-8_53
M3 - Conference contribution
AN - SCOPUS:55349086227
SN - 3540859195
SN - 9783540859192
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 429
EP - 436
BT - Progress in Pattern Recognition, Image Analysis and Applications - 13th Iberoamerican Congress on Pattern Recognition, CIARP 2008, Proceedings
Y2 - 9 September 2008 through 12 September 2008
ER -