DocumentCode :
1586270
Title :
Application of Particle Swarm Optimization Based BP Neural Network on Engineering Project Risk Evaluating
Author :
Chang, Chun-guang ; Wang, Ding-wei ; Liu, Ya-chen ; Qi, Bao-ku
Author_Institution :
Shenyang Jianzhu Univ., Shenyang
Volume :
1
fYear :
2007
Firstpage :
750
Lastpage :
754
Abstract :
The purpose of this paper is to improve the risk evaluating quality of engineering project. The topology structure of particle swarm optimization (PSO) based BP (PSOBP) neural network is described, the principle of PSOBP neural network is introduced, and the implement step of PSOBP neural network is given. The combination algorithm is applied to risk evaluating for the engineering project, and its result is compared with that of conventional BP neural network. The comparing result shows that PSOBP neural network fits to complex system such as risk evaluating for engineering project, it improves in a certain extent on training speed and precision, it can improve the quality of engineering project risk evaluating, and it fits to solve some problems in which evaluating indexes weights are difficult to be determined or there exists complex non-linear relation among them.
Keywords :
backpropagation; neural nets; particle swarm optimisation; project management; risk analysis; topology; BP neural network; engineering project risk evaluating; particle swarm optimization; risk evaluating quality; topology structure; Convergence; Engineering management; Information science; Management training; Network topology; Neural networks; Particle swarm optimization; Project management; Quality management; Risk management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.259
Filename :
4344291
Link To Document :
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