DocumentCode :
3174184
Title :
The fitting method of parameter distributions in Geotechnical engineering under small sample
Author :
Qingnian, Yang ; Yuzhou, Sima
Author_Institution :
Dept. of Civil Eng., Nanyang Inst. of Technol., Nanyang, China
fYear :
2011
fDate :
8-10 Aug. 2011
Firstpage :
7366
Lastpage :
7369
Abstract :
The deficiencies existing in Geotechnical parameters distribution fitting using the classical probability distribution are analyzed and the stochastic weighting method is employed to improve the the small samples of Geotechnical parameters into big samples, thus sloving the problems caused by the small sample. The maximum entropy principle and the big samples improving from small sample are used to generate probability density functions of Geotechnical parameters. It is more rational and scientific with the method proposed in the paper through the Kolmogorov-Smirnov Test. It is demonstrated through the example that the method presented in this paper not only successfully escapes the reliance of the classical probability distribution functions, but also make the computation result more closed to the fact due to the data coming from the big sample improving from the small sample, which has important engineering significance.
Keywords :
geotechnical engineering; maximum entropy methods; probability; Kolmogorov-Smirnov test; classical probability distribution functions; fitting method; geotechnical engineering; maximum entropy principle; parameter distributions; stochastic weighting method; Entropy; Equations; Fitting; Mathematical model; Probability distribution; Reliability; Rocks; geotechnical parameter; probability distribution; small samples; stochastic weighted; the maximum entropy principle;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), 2011 2nd International Conference on
Conference_Location :
Deng Leng
Print_ISBN :
978-1-4577-0535-9
Type :
conf
DOI :
10.1109/AIMSEC.2011.6010605
Filename :
6010605
Link To Document :
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