The Study on the Gray Neural Network Model and Its Application in the Prediction

Author

Peng Wen-tao ; Wu Jun ; Chen Ying-qing ; Xiao Xuan ; Zhong Luo

Author_Institution

Coll. of Civil Eng. & Archit., Wuhan Univ. of Technol., Wuhan, China

fYear

2009

fDate

19-20 Dec. 2009

Firstpage

28

Lastpage

30

Abstract

The study on the bearing capacity and settlement is important to a project. It is useful and concrete to develop a model with some intelligent methods in artificial intelligence area for the prediction of some big structure projects. The validity of the models has been proved by some civil engineering practices. Therefore, the research of bearing capacity and settlement characteristics of rigid pile composite foundation has been the focus of the basic engineering research area in foundations. This paper established a model based on the Gray RBF neutral network which is a combination of gray model and RBF neutral network model and realized the model with Matlab7.0.

Keywords

artificial intelligence; civil engineering computing; radial basis function networks; Gray RBF neutral network; Matlab7.0; artificial intelligence; big structure projects; civil engineering practices; gray neural network model; intelligent methods; rigid pile composite foundation; Artificial intelligence; Association rules; Civil engineering; Data mining; Differential equations; Knowledge engineering; Mathematical model; Neural networks; Predictive models; Software engineering; Gray neutral network; Prediction model; pile capacity;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge Engineering and Software Engineering, 2009. KESE '09. Pacific-Asia Conference on

Conference_Location

Shenzhen

Print_ISBN

978-0-7695-3916-4

Type

conf

DOI

10.1109/KESE.2009.15

Filename

5383631