DocumentCode :
668634
Title :
Study on prediction model of building construction safety accidents based on GA-SVM
Author :
Feng Yajuan ; Cui Jia
Author_Institution :
Bus. Adm. Inst., Liaoning Tech. Univ., Huludao, China
Volume :
2
fYear :
2013
fDate :
23-24 Nov. 2013
Firstpage :
460
Lastpage :
462
Abstract :
In the Genetic algorithm and Support vector machine prediction method, the two methods are combined and applied to the construction safety accident prediction. Select main factors leading to construction safety accident, and then prediction model of construction safety accident is constructed. The model uses simulation cases as the training sample to determine the parameters in GA-SVM, and to carry on the forecast. The GA-SVM, SVM standard, BP neural network, fuzzy clustering and various methods are compared. The results show that: Prediction model based on GA - SVM has the rationality and effectiveness, and it highlights the characteristics of prediction results with high precision and strong stability, so there is practical value to construction.
Keywords :
backpropagation; civil engineering computing; fuzzy set theory; genetic algorithms; industrial accidents; neural nets; occupational safety; production engineering computing; support vector machines; BP neural network; GA-SVM; Support vector machine prediction method; building construction safety accident prediction; fuzzy clustering; genetic algorithm; Accidents; Buildings; Genetic algorithms; Predictive models; Safety; Support vector machines; Training; Genetic algorithm (GA); Support vector machine (SVM); construction safety prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management, Innovation Management and Industrial Engineering (ICIII), 2013 6th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-3985-5
Type :
conf
DOI :
10.1109/ICIII.2013.6703186
Filename :
6703186
Link To Document :
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