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Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05)
A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem
Dalian, China
December 05-December 08
ISBN: 0-7695-2405-2
ASCII Text
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Lei YANG, Yu DAI, Bin ZHANG, Yan GAO, "A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem," Parallel and Distributed Computing Applications and Technologies, International Conference on, pp. 925-929, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005.
 
 
BibTex
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@article{ 10.1109/PDCAT.2005.13,
author = {Lei YANG and Yu DAI and Bin ZHANG and Yan GAO},
title = {A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem},
journal ={Parallel and Distributed Computing Applications and Technologies, International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2405-2},
pages = {925-929},
doi = {http://doi.ieeecomputersociety.org/10.1109/PDCAT.2005.13},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Parallel and Distributed Computing Applications and Technologies, International Conference on
TI - A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem
SN - 0-7695-2405-2
SP925
EP929
A1 - Lei YANG,
A1 - Yu DAI,
A1 - Bin ZHANG,
A1 - Yan GAO,
PY - 2005
KW - null
VL - 0
JA - Parallel and Distributed Computing Applications and Technologies, International Conference on
ER -
 
Lei YANG, Northeastern University, China
Yu DAI, Northeastern University, China
Bin ZHANG, Northeastern University, China
Yan GAO, Northeastern University, China
For the widely use of multistage decision-making problem in our normal life such as in the new research area of dynamic selection of composite web services, this paper exerts all its effort on proposing a new approach to solve such problem. Motivated by neural networks? high parallel performance and Genetic Algorithm?s powerful computation, a novel Genetic Algorithm optimized neural network is proposed in this paper for this task. In order to make this algorithm more adaptable for multistage decision-making problem, a new neural network structure for implementing the algorithm is proposed which is a modification to the one used by Thomopoulos or Rauch and Winarske.
Citation:
Lei YANG, Yu DAI, Bin ZHANG, Yan GAO, "A Genetic Algorithm Optimized New Structured Neural Network for Multistage Decision-Making Problem," pdcat, pp.925-929, Sixth International Conference on Parallel and Distributed Computing Applications and Technologies (PDCAT'05), 2005
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