Title :
A Modular Neural Networks ensembling method based on fuzzy decision-making
Author :
Bo, Ying-Chun ; Qiao, Jun-fei ; Yang, Gang
Author_Institution :
Coll. of Electron. & Control Eng., Beijing Univ. of Technol., Beijing, China
Abstract :
This paper integrates the ideas of "divide and conquer" and "put the heads together", and proposes a method of selecting sub-networks on-line based on fuzzy decision making. For a given input, this method calculates the distances between the input and the centers of sub-networks firstly, and then obtains the fuzzy member degree based on distance measure, finally realizes on-line sub-networks selection by fuzzy decision-making. The group of selected sub-networks varies with different inputs. It ensembles multi sub-networks by linear method. The weights of sub-networks are optimized by reconstructing the sample space. The simulation results suggest that this method can improve the precision and generalization ability effectively.
Keywords :
decision making; divide and conquer methods; fuzzy set theory; neural nets; optimisation; distance measure; divide and conquer method; fuzzy decision making; fuzzy member degree; generalization ability; linear method; modular neural network ensembling method; online subnetwork selection; precision ability; put the head together method; sample space reconstruction; subnetwork weight optimization; Artificial neural networks; Decision making; Mathematical model; Multi-layer neural network; Noise; Optimization; Training; Fuzzy Decision-making; Modular Neural Networks; Weights Optimization; self-adaptive integration;
Conference_Titel :
Electric Information and Control Engineering (ICEICE), 2011 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-8036-4
DOI :
10.1109/ICEICE.2011.5777823