Artificial neural network for stress-strain behavior of sandy soils: Knowledge based verification

M. Banimahd, S. S. Yasrobi, P. K. Woodward

    Research output: Contribution to journalArticle

    57 Citations (Scopus)

    Abstract

    In this paper, artificial neural networks (ANNs) are applied to model the stress-strain behavior of in situ sandy soils containing nonplastic fines. A main drawback of these types of models is discussed, i.e. an ANN based model gives no information how the model inputs affect the output. A systematic approach is therefore presented to acquire and verify the stored knowledge of a general ANN based constitutive soil model. Sensitivities of the output to corresponding inputs are defined mathematically. A sensitivity analysis is then performed to extract the dominant rules of the proposed model, which compare favorably with experimental observations. © 2005 Elsevier Ltd. All rights reserved.

    Original languageEnglish
    Pages (from-to)377-386
    Number of pages10
    JournalComputers and Geotechnics
    Volume32
    Issue number5
    DOIs
    Publication statusPublished - Jul 2005

    Keywords

    • Artificial neural network
    • Sandy soils
    • Sensitivity analysis
    • Stress-strain
    • Undrained behavior

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