Sinopsis
Traditional analysis methods used in Structural Engineering are reliable and can be successfully applied by solving several numerical equations. Another alternative analytical modeling method is Artificial Neural Networks (ANNs), which capture the numerical equations between its nodes and no formal formula is observable within the network generation. ANN system is an acceptable method in predicting experimental results. In this book, FBNN and GRNN are generated to predict the load-deflection analysis in the one-way non-strengthened and Carbon Fiber Reinforced Polymer (CFRP) strengthened RC slab. The GRNN was applied for situation where training data is insufficient for network generation. In addition, GRNN is also applied for the mechanical strength prediction of lightweight concrete and mortar.
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Acerca del autor
Dr. Seyed Vahid Razavi tosee is a holder of academic position in Structural Engineering Department 0f Joundi-shapor University of Technology, Dezful, Iran. His main areas of research includes Structural Engineering, Neural Networks, Smart Structures, Structural dynamics, and more recently dynamic assessment and health monitoring of bridges.
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Using Generalized Regression Neural Network in Structural Engineering
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Traditional analysis methods used in Structural Engineering are reliable and can be successfully applied by solving several numerical equations. Another alternative analytical modeling method is Artificial Neural Networks (ANNs), which capture the numerical equations between its nodes and no formal formula is observable within the network generation. ANN system is an acceptable method in predicting experimental results. In this book, FBNN and GRNN are generated to predict the load-deflection analysis in the one-way non-strengthened and Carbon Fiber Reinforced Polymer (CFRP) strengthened RC slab. The GRNN was applied for situation where training data is insufficient for network generation. In addition, GRNN is also applied for the mechanical strength prediction of lightweight concrete and mortar. 116 pp. Englisch. Nº de ref. del artículo: 9783639661255
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Using Generalized Regression Neural Network in Structural.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Razavi Tosee Seyed VahidDr. Seyed Vahid Razavi tosee is a holder of academic position in Structural Engineering Department 0f Joundi-shapor University of Technology, Dezful, Iran. His main areas of research includes Structural Engin. Nº de ref. del artículo: 4996447
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Using Generalized Regression Neural Network in Structural Engineering
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Scholars' Press Aug 2014, 2014
ISBN 10: 3639661257
ISBN 13: 9783639661255
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Traditional analysis methods used in Structural Engineering are reliable and can be successfully applied by solving several numerical equations. Another alternative analytical modeling method is Artificial Neural Networks (ANNs), which capture the numerical equations between its nodes and no formal formula is observable within the network generation. ANN system is an acceptable method in predicting experimental results. In this book, FBNN and GRNN are generated to predict the load-deflection analysis in the one-way non-strengthened and Carbon Fiber Reinforced Polymer (CFRP) strengthened RC slab. The GRNN was applied for situation where training data is insufficient for network generation. In addition, GRNN is also applied for the mechanical strength prediction of lightweight concrete and mortar.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. Nº de ref. del artículo: 9783639661255
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Using Generalized Regression Neural Network in Structural Engineering
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Traditional analysis methods used in Structural Engineering are reliable and can be successfully applied by solving several numerical equations. Another alternative analytical modeling method is Artificial Neural Networks (ANNs), which capture the numerical equations between its nodes and no formal formula is observable within the network generation. ANN system is an acceptable method in predicting experimental results. In this book, FBNN and GRNN are generated to predict the load-deflection analysis in the one-way non-strengthened and Carbon Fiber Reinforced Polymer (CFRP) strengthened RC slab. The GRNN was applied for situation where training data is insufficient for network generation. In addition, GRNN is also applied for the mechanical strength prediction of lightweight concrete and mortar. Nº de ref. del artículo: 9783639661255
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Using Generalized Regression Neural Network in Structural Engineering
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Taschenbuch. Condición: Neu. Using Generalized Regression Neural Network in Structural Engineering | Seyed Vahid Razavi Tosee (u. a.) | Taschenbuch | 116 S. | Englisch | 2014 | Scholars' Press | EAN 9783639661255 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Nº de ref. del artículo: 105128223
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