INTELLIGENT MODELS in geotechnical engineering

Pijush Samui

ISBN 10: 3838348761 / ISBN 13: 9783838348766

Editore: LAP LAMBERT Academic Publishing Feb 2010, 2010

Riguardo questo articolo

Neuware -The objective of this book is to develop intelligent models [geostatistic, artificial neural network (ANN) and support vector machine(SVM)] to estimate corrected standard penetration test (SPT) value, Nc, in the three dimensional (3D) subsurface of Bangalore. The present book also highlights the capability of SVM over the developed geostatistic models (simple kriging, ordinary kriging and disjunctive kriging) and ANN models. Further in this book, liquefaction susceptibility is evaluated from Standard Penetration Test (SPT), Cone Penetration Test (CPT) and Shear Wave (Vs) data using ANN and SVM. In this book, an attempt has also been made to evaluate geotechnical site characterization by carrying out in situ tests using different in situ techniques such as CPT, SPT and multi channel analysis of surface wave (MASW) techniques. SVM model has been also adopted to determine over consolidation ratio (OCR) based on piezocone data. SVM model outperforms all the available methods for OCR prediction.Books on Demand GmbH, Überseering 33, 22297 Hamburg 348 pp. Englisch.

Codice articolo 9783838348766

Dati bibliografici

• Titolo: INTELLIGENT MODELS in geotechnical engineering
• Editore: LAP LAMBERT Academic Publishing Feb 2010
• Data di pubblicazione: 2010
• Lingua: Inglese
• ISBN 10: 3838348761
• ISBN 13: 9783838348766
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 21 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 21 millimetri di profondità
• Peso: 536 grammi

Descrizione articolo

Riassunto

The objective of this book is to develop intelligent models [geostatistic, artificial neural network (ANN) and support vector machine(SVM)] to estimate corrected standard penetration test (SPT) value, Nc, in the three dimensional (3D) subsurface of Bangalore. The present book also highlights the capability of SVM over the developed geostatistic models (simple kriging, ordinary kriging and disjunctive kriging) and ANN models. Further in this book, liquefaction susceptibility is evaluated from Standard Penetration Test (SPT), Cone Penetration Test (CPT) and Shear Wave (Vs) data using ANN and SVM. In this book, an attempt has also been made to evaluate geotechnical site characterization by carrying out in situ tests using different in situ techniques such as CPT, SPT and multi channel analysis of surface wave (MASW) techniques. SVM model has been also adopted to determine over consolidation ratio (OCR) based on piezocone data. SVM model outperforms all the available methods for OCR prediction.