Isbn: 9786206065111 - simulation using artificial neural networks in geotechnical engineering (17 resultados)

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Taschenbuch. Condición: Neu. Simulation using artificial neural networks in geotechnical engineering | Amal Benali | Taschenbuch | Englisch | 2023 | Our Knowledge Publishing | EAN 9786206065111 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the rapid technological and industrial development that the world has seen, particularly in construction technology with these huge oil platforms in the depths of the ocean or desert. This requires an adequate load-bearing structural system, capable of distributing forces from one level to another until they reach the foot of the structure, known as the foundation. The important role of deep foundations in transmitting service loads from the superstructure to the deep soil bearing layers has prompted the use of empirical and semi-empirical methods for the axial bearing capacity design of a pile. Alternatively, artificial neural networks (ANNs) have recently been used to predict the ultimate capacity of piles based on in situ tests. Very recently, several researchers have successfully used the RNAs artificial neural network approach for the development of integrated models in conjunction with other probabilistic and evolutionary methods. 52 pp. Englisch.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the rapid technological and industrial development that the world has seen, particularly in construction technology with these huge oil platforms in the depths of the ocean or desert. This requires an adequate load-bearing structural system, capable of distributing forces from one level to another until they reach the foot of the structure, known as the foundation. The important role of deep foundations in transmitting service loads from the superstructure to the deep soil bearing layers has prompted the use of empirical and semi-empirical methods for the axial bearing capacity design of a pile. Alternatively, artificial neural networks (ANNs) have recently been used to predict the ultimate capacity of piles based on in situ tests. Very recently, several researchers have successfully used the RNAs artificial neural network approach for the development of integrated models in conjunction with other probabilistic and evolutionary methods.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the rapid technological and industrial development that the world has seen, particularly in construction technology with these huge oil platforms in the depths of the ocean or desert. This requires an adequate load-bearing structural system, capable of distributing forces from one level to another until they reach the foot of the structure, known as the foundation. The important role of deep foundations in transmitting service loads from the superstructure to the deep soil bearing layers has prompted the use of empirical and semi-empirical methods for the axial bearing capacity design of a pile. Alternatively, artificial neural networks (ANNs) have recently been used to predict the ultimate capacity of piles based on in situ tests. Very recently, several researchers have successfully used the RNAs artificial neural network approach for the development of integrated models in conjunction with other probabilistic and evolutionary methods.OmniScriptum SRL, Str. Armeneasca 28/1, office 1, 2012 Chisinau 52 pp. Englisch.…