Journal
INDIAN GEOTECHNICAL JOURNAL
Volume 45, Issue 3, Pages 349-359Publisher
SPRINGER INDIA
DOI: 10.1007/s40098-014-0142-2
Keywords
Lateral loaded pile; Clay; Genetic programming; Statistical method
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This study presents the development of predictive models of lateral load capacity of pile in clay using artificial intelligence techniques; genetic programming and multivariate adaptive regression spline. The developed models are compared with different empirical models, artificial neural network (ANN) and support vector machine (SVM) models in terms of different statistical criteria. A ranking system is presented to evaluate present models with respect to above models. Model equations are presented and are found to be more compact compared to ANN and SVM models. A sensitivity analysis is made to identify the important inputs contributing to the lateral load capacity of pile.
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