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INTELLIGENT MODELS in geotechnical engineering: INTELLIGENT MODELS in geotechnical engineering - Softcover
Inhaltsangabe
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.
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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.
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INTELLIGENT MODELS in geotechnical engineering
Verlag:
LAP LAMBERT Academic Publishing Feb 2010, 2010
ISBN 10: 3838348761
ISBN 13: 9783838348766
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Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. 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. Artikel-Nr. 9783838348766
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