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Workshop on Intelligent Information Technology Application (IITA 2007)
Research on Optimal-Selection Model Based on Genetic Algorithm Optimizing Design for Electric Plant Construction Projects
Zhang Jiajia, China
December 02-December 03
ISBN: 0-7695-3063-X
ASCII Text
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Zhibin Liu, "Research on Optimal-Selection Model Based on Genetic Algorithm Optimizing Design for Electric Plant Construction Projects," Intelligent Information Technology Applications, 2007 Workshop on, pp. 14-17, Workshop on Intelligent Information Technology Application (IITA 2007), 2007.
 
 
BibTex
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@article{ 10.1109/IITA.2007.32,
author = {Zhibin Liu},
title = {Research on Optimal-Selection Model Based on Genetic Algorithm Optimizing Design for Electric Plant Construction Projects},
journal ={Intelligent Information Technology Applications, 2007 Workshop on},
volume = {0},
year = {2007},
isbn = {0-7695-3063-X},
pages = {14-17},
doi = {http://doi.ieeecomputersociety.org/10.1109/IITA.2007.32},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Intelligent Information Technology Applications, 2007 Workshop on
TI - Research on Optimal-Selection Model Based on Genetic Algorithm Optimizing Design for Electric Plant Construction Projects
SN - 0-7695-3063-X
SP14
EP17
A1 - Zhibin Liu,
PY - 2007
KW - null
VL - 0
JA - Intelligent Information Technology Applications, 2007 Workshop on
ER -
 
The electric plant construction projects evaluation is a complex, multi-factor, multi-index decision-making problem. In order to evaluate the electric plant construction projects scientifically and accurately, this paper proposes the optimal model based on improved genetic algorithm. The model has the advantages of self-learning, self-organizing and self-adapting, avoids the subjective mistakes in the evaluation process, and improves the evaluating accuracy greatly. The evaluation of 5 electric plant construction projects in National Electric Company shows that the results given by this model are reliable, and this method to evaluate the electric plant construction projects is feasible and effective.
Citation:
Zhibin Liu, "Research on Optimal-Selection Model Based on Genetic Algorithm Optimizing Design for Electric Plant Construction Projects," iita, pp.14-17, Workshop on Intelligent Information Technology Application (IITA 2007), 2007
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