[1]BO Yingchun,QIAO Junfei,YANG Gang.A multimodule cooperative neural network[J].CAAI Transactions on Intelligent Systems,2011,6(3):225-230.
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A multimodule cooperative neural network

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 3 Page number: 225-230 Column: 学术论文—机器学习 Public date: 2011-06-25
Title:
A multimodule cooperative neural network
Author(s):
BO Yingchun;  QIAO Junfei;  YANG Gang 
College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
Keywords:
neural networks;  conditional fuzzy clustering method;  multimodules;  subnets selection
CLC:
TP183
DOI:
-
Abstract:
Aiming to solve the problems of long training time, low precision in processing complex problem, and a local minimum in single neural networks, a multimodule cooperative neural network (MMCNN) was proposed. Its structure has hierarchical character. Sample data was first detached by the fuzzy clustering method, and then the neural network was partitioned into several subnets based on the clustering results. The linking weights were elicited by solving equations. For a given input data, some multimodules were selected to deal with it. The approximating performance was improved by combining divideandconquer and learning ensemble strategies. A subnet selection method was designed based on distance measurements. Simulation results demonstrate that a multimodule cooperative neural network can heighten approximating ability effectively for complicated problems, and the training time is faster than in a single backpropagation neural network.
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