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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - 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. 348 pp. Englisch. N° de réf. du vendeur 9783838348766
Quantité disponible : 2 disponible(s)
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
Paperback. Etat : Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. N° de réf. du vendeur ERICA75838383487616
Quantité disponible : 1 disponible(s)
Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Samui PijushDr. Pijush Samui is an associate professor at Center for Disaster Mitigation and Management in Vellore Institute of Technology, Vellore, India. He has published 53 technical papers in journals and conferences. He is . N° de réf. du vendeur 5415303
Quantité disponible : Plus de 20 disponibles
Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. INTELLIGENT MODELS in geotechnical engineering | INTELLIGENT MODELS in geotechnical engineering | Pijush Samui (u. a.) | Taschenbuch | 348 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838348766 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 101073127
Quantité disponible : 5 disponible(s)
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 348 pp. Englisch. N° de réf. du vendeur 9783838348766
Quantité disponible : 1 disponible(s)
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783838348766
Quantité disponible : 1 disponible(s)