A Soft-Roadbed Settlement Prediction Model Based on RBFNN

Xiang Hua Peng; Zhi Cha Wang; Min Yu

doi:10.4028/www.scientific.net/AMR.639-640.535

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 639-640A Soft-Roadbed Settlement Prediction Model Based...

A Soft-Roadbed Settlement Prediction Model Based on RBFNN

Abstract:

The control of subgrade settlement has been the main influencing factor on highroad pavement quality, so estimating settlement amount after construction based on designed embankment height and planning the construction filling height beforehand through the settlement prediction is a very important work. Because of the complex coupling properties and high nonlinear characteristics of the factors influencing foundation settlement, a soft-roadbed settlement prediction model based on RBFNN (Radial Basis Function Neural Network) is proposed, combining the global fitting properties of RBFNN. The analysis shows that the model owns good fitting property and high prediction precise, and certain practical value.

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Periodical:

Advanced Materials Research (Volumes 639-640)

Pages:

535-538

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.639-640.535

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Online since:

January 2013

Authors:

Xiang Hua Peng, Zhi Cha Wang, Min Yu

Keywords:

Prediction Model, RBF Neural Network, Soft-Roadbed, Subgrade Settlement

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