TY - GEN
T1 - A parsimonious radial basis function-based neural network for data classification
AU - Tan, Shing Chiang
AU - Lim, Chee Peng
AU - Watada, Junzo
PY - 2016
Y1 - 2016
N2 - The radial basis function neural network trained with a dynamic decay adjustment (known as RBFNDDA) algorithm exhibits a greedy insertion behavior as a result of recruiting many hidden nodes for encoding information during its training process. In this chapter, a new variant RBFNDDA is proposed to rectify such deficiency. Specifically, the hidden nodes of RBFNDDA are re-organized through the supervised Fuzzy ARTMAP (FAM) classifier, and the parameters of these nodes are adapted using the Harmonic Means (HM) algorithm. The performance of the proposed model is evaluated empirically using three benchmark data sets. The results indicate that the proposed model is able to produce a compact network structure and, at the same time, to provide high classification performances.
AB - The radial basis function neural network trained with a dynamic decay adjustment (known as RBFNDDA) algorithm exhibits a greedy insertion behavior as a result of recruiting many hidden nodes for encoding information during its training process. In this chapter, a new variant RBFNDDA is proposed to rectify such deficiency. Specifically, the hidden nodes of RBFNDDA are re-organized through the supervised Fuzzy ARTMAP (FAM) classifier, and the parameters of these nodes are adapted using the Harmonic Means (HM) algorithm. The performance of the proposed model is evaluated empirically using three benchmark data sets. The results indicate that the proposed model is able to produce a compact network structure and, at the same time, to provide high classification performances.
KW - Adaptive resonance theory
KW - Classification
KW - Harmonic mean algorithm
KW - Radial basis function neural network
UR - http://www.scopus.com/inward/record.url?scp=84951745921&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84951745921&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-21209-8_4
DO - 10.1007/978-3-319-21209-8_4
M3 - Conference contribution
AN - SCOPUS:84951745921
SN - 9783319212081
VL - 42
T3 - Smart Innovation, Systems and Technologies
SP - 49
EP - 60
BT - Smart Innovation, Systems and Technologies
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Intelligent Decision Technologies, 2013
Y2 - 26 June 2013 through 28 June 2013
ER -