Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Prediction of Earthquake-Induced Liquefaction State in Embankment Dams Using Back-Propagation Neural Network
One of the most seismic damaging events in earth dams is a phenomenon called Liquefaction. In this research, a Feed-forward Back-propagation Neural Network (FBNN) model as a classification tool, with one output parameter which represents the occurrence and non-occurrence of earthquake-induced liquefaction state in embankment dams, was developed. A total of 152 embankment dam datasets were considered: 42 dams that liquefied and 110 dams that did not liquefy. The accuracy of the (7-10-1) developed FBNN model is more than 94% for this problem. Finally, the developed model has an adequate accuracy in prediction of the liquefaction state of embankment dams under earthquake loading, and this might prove to be a useful alternative, with distinct advantages over the conventional methods.
Prediction of Earthquake-Induced Liquefaction State in Embankment Dams Using Back-Propagation Neural Network
One of the most seismic damaging events in earth dams is a phenomenon called Liquefaction. In this research, a Feed-forward Back-propagation Neural Network (FBNN) model as a classification tool, with one output parameter which represents the occurrence and non-occurrence of earthquake-induced liquefaction state in embankment dams, was developed. A total of 152 embankment dam datasets were considered: 42 dams that liquefied and 110 dams that did not liquefy. The accuracy of the (7-10-1) developed FBNN model is more than 94% for this problem. Finally, the developed model has an adequate accuracy in prediction of the liquefaction state of embankment dams under earthquake loading, and this might prove to be a useful alternative, with distinct advantages over the conventional methods.
Prediction of Earthquake-Induced Liquefaction State in Embankment Dams Using Back-Propagation Neural Network
Environ Sci Eng
Ksibi, Mohamed (Herausgeber:in) / Ghorbal, Achraf (Herausgeber:in) / Chakraborty, Sudip (Herausgeber:in) / Chaminé, Helder I. (Herausgeber:in) / Barbieri, Maurizio (Herausgeber:in) / Guerriero, Giulia (Herausgeber:in) / Hentati, Olfa (Herausgeber:in) / Negm, Abdelazim (Herausgeber:in) / Lehmann, Anthony (Herausgeber:in) / Römbke, Jörg (Herausgeber:in)
Euro-Mediterranean Conference for Environmental Integration ; 2019 ; Sousse, Tunisia
Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions (2nd Edition) ; Kapitel: 321 ; 2051-2055
10.04.2021
5 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Embankment dam , Earthquake-induced liquefaction state , Back-propagation neural network , Simplified dynamic analysis Environment , Environment, general , Climate Change/Climate Change Impacts , Medical and Radiation Physics , Corporate Environmental Management , Environmental Science and Engineering , Earth and Environmental Science
Liquefaction Analyses for Embankment Dams
| British Library Conference Proceedings | 1987
Embankment dams - problems of earthquake
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Case History-Based Liquefaction Analysis of Embankment Dams
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Nonlinear Deformation Analyses of Liquefaction Effects on Embankment Dams
| British Library Conference Proceedings | 2015
| British Library Conference Proceedings | 2005