Articoli correlati a Dynamic Neural Network for Predicting Creep of Structural...
Dynamic Neural Network for Predicting Creep of Structural Masonry: An Application of Artificial Intelligence Techniques - Brossura
Sinossi
One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sull'autore
Mustafa Mohammed Abed has obtained his M.Sc degree in Civil and Structural Engineering from National University of Malaysia in 2011. He has worked as a Consultant Engineer in different international projects in the field of Construction Industry. He is the author of several articles published in reputed international journals.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Dynamic Neural Network for Predicting Creep of Structural...
Immagini fornite dal venditore
Dynamic Neural Network for Predicting Creep of Structural Masonry
Editore:
LAP LAMBERT Academic Publishing Feb 2012, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Nuovo
Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models. 96 pp. Englisch. Codice articolo 9783846588208
Compra nuovo
EUR 49,00
Spedizione EUR 23,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 2 disponibili
Immagini fornite dal venditore
Dynamic Neural Network for Predicting Creep of Structural Masonry : An Application of Artificial Intelligence Techniques
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Nuovo
Taschenbuch
Da: AHA-BUCH GmbH, Einbeck, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models. Codice articolo 9783846588208
Compra nuovo
EUR 54,70
Spedizione EUR 35,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Dynamic Neural Network for Predicting Creep of Structural Masonry
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Nuovo
Brossura
Da: moluna, Greven, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abed Mustafa MohammedMustafa Mohammed Abed has obtained his M.Sc degree in Civil and Structural Engineering from National University of Malaysia in 2011. He has worked as a Consultant Engineer in different international projects in t. Codice articolo 5501535
Compra nuovo
EUR 41,05
Spedizione EUR 48,99
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: Più di 20 disponibili
Immagini fornite dal venditore
Dynamic Neural Network for Predicting Creep of Structural Masonry
Editore:
LAP LAMBERT Academic Publishing Feb 2012, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Nuovo
Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -One of the inherent modeling problems in structural engineering is creep of quasi-brittle materials (e.g., concrete and masonry). The creep strain represents the non-instantaneous strain that occurs with time when the stress is sustained. Several creep models with limited accuracy have been developed within the last few decades to predict creep of concrete and masonry structures. The stochastic nature of creep deformation and its reliance on a large number of uncontrolled parameters (e.g., relative humidity, age of loading, stress level) makes the process of prediction difficult, and yet accurate mathematical model almost impossible. This study investigates the potential use of Dynamic Neural Network (DNN) for predicting creep of structural masonry. The main motive of use DNN is that DNN could memorize the sequential or time-varying patterns while training process. Thus, DNN becomes more capable of capturing the time-dependent of creep deformation than the static networks. The results showed that the developed DNN models are able to predict the creep deformation with an excellent level of accuracy compared with that of conventional methods and the static networks models.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 96 pp. Englisch. Codice articolo 9783846588208
Compra nuovo
EUR 49,00
Spedizione EUR 60,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 1 disponibili
Immagini fornite dal venditore
Dynamic Neural Network for Predicting Creep of Structural Masonry | An Application of Artificial Intelligence Techniques
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Nuovo
Taschenbuch
Da: preigu, Osnabrück, Germania
Valutazione del venditore 5 su 5 stelle
Taschenbuch. Condizione: Neu. Dynamic Neural Network for Predicting Creep of Structural Masonry | An Application of Artificial Intelligence Techniques | Mustafa Mohammed Abed | Taschenbuch | 96 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783846588208 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 106631634
Compra nuovo
EUR 43,40
Spedizione EUR 70,00
Spedito da Germania a U.S.A.
Spedito da Germania a U.S.A.
Quantità: 5 disponibili
Foto dell'editore
Dynamic Neural Network for Predicting Creep of Structural Masonry: An Application of Artificial Intelligence Techniques
Editore:
LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3846588202
ISBN 13: 9783846588208
Antico o usato
Paperback
Da: Mispah books, Redhill, SURRE, Regno Unito
Valutazione del venditore 4 su 5 stelle
Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Codice articolo ERICA75838465882025
Compra usato
EUR 142,14
Spedizione EUR 30,00
Spedito da Regno Unito a U.S.A.
Spedito da Regno Unito a U.S.A.
Quantità: 1 disponibili