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Application of Artificial Neural Network in Estimation of Foundation Soil Liquefaction

Author: XueXinHua
Tutor: LiuHongJun
School: Ocean University of China
Course: Environmental Engineering
Keywords: Artificial Neural Networks Earthquake Liquefaction Silt
CLC: P315.9
Type: Master's thesis
Year: 2004
Downloads: 171
Quote: 4
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Abstract


Earthquake engineering foundation soil liquefaction is an important problem , its occurrence , the development process is a complex process . Foundation soil liquefaction impact of many factors , randomness , and was among the factors highly nonlinear . Traditional discriminant method is summarized in the macro- seismic damage phenomena and laboratory tests on the basis of analysis , statistics obtained , there is a certain practicality , but there are also some limitations , the conclusions of the reliability needed to improve . Analysis traditional methods based on , proposed the establishment of an anthropogenic factors , quantitative and qualitative indicators to accommodate in one Liquefaction and evaluation model is necessary . This paper describes the basic principles of artificial neural networks and implementation techniques , and preparation of the artificial neural network program based on the use of Matlab6.5 : 1) the preparation of the BP neural network program , additional momentum , learning rate , momentum parameter in adaptive adjustment error correction process , to improve the speed of training . 2) compared Toolbox RBF network , network learning algorithm is the key to improve network performance . Dynamic triaxial test results in this article in accordance with the indoor consider various factors , Liquefaction artificial neural network model , compared with the traditional method , in the case of reasonable data , the neural network can draw the following conclusions : 1) quickly achieve higher prediction accuracy than traditional methods . Establish Liquefaction network model is scientific and effective . 2 ) network model can reveal the intrinsic relationship between the structure and parameters of running , the input -output relationship is quantified , and the size of the contribution rate based on a single factor of subsoil liquefaction principal component analysis , not only to verify the traditional methods of reasonable and specification method is suggested.

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CLC: > Astronomy,Earth Sciences > Geophysics > Earth ( rock circles ) physics ( geophysics ) > Seismology > Engineering seismology
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