The book is subdivided into five chapters. Each chapter is briefly described as follows: Chapter 1 gives a general background of the subject matter and serves as an introductory chapter. It incorporates the background of the study, problem statement, objectives of the research and a brief on the outline. Chapter 2 comprises of information relevant to this work. It includes background information on concrete characteristics, self compacting concrete, artificial intelligence, and the application of artificial neural networks in concrete research. Chapter 3 is devoted to the methodology adopted to achieve the objectives of the research. This includes investigation of the best network used for the prediction of self compacting concrete characteristics by using published experimental data. Chapter 4 describes the details on modelling and programming. It also presents all steps in designing artificial neural network and comprises the results of the main proposed training functions to obtain the best network. Chapter 5 contains the conclusions arrived at and gives the recommendations for future works.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
The book is subdivided into five chapters. Each chapter is briefly described as follows: Chapter 1 gives a general background of the subject matter and serves as an introductory chapter. It incorporates the background of the study, problem statement, objectives of the research and a brief on the outline. Chapter 2 comprises of information relevant to this work. It includes background information on concrete characteristics, self compacting concrete, artificial intelligence, and the application of artificial neural networks in concrete research. Chapter 3 is devoted to the methodology adopted to achieve the objectives of the research. This includes investigation of the best network used for the prediction of self compacting concrete characteristics by using published experimental data. Chapter 4 describes the details on modelling and programming. It also presents all steps in designing artificial neural network and comprises the results of the main proposed training functions to obtain the best network. Chapter 5 contains the conclusions arrived at and gives the recommendations for future works.
Civil and Energy Saving Engineer
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Papzan AliCivil and Energy Saving EngineerThe book is subdivided into five chapters. Each chapter is briefly described as follows: Chapter 1 gives a general background of the subject matter and serves as an introductory chapter. N° de réf. du vendeur 5139021
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Taschenbuch. Etat : Neu. Forecasting the Compressive Strength of SCC by ANNs | The Application of Artificial Neural Networks to Predict the Compressive Strength of Self-Compacting Concretes | Ali Papzan (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659199202 | 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 106309225
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book is subdivided into five chapters. Each chapter is briefly described as follows: Chapter 1 gives a general background of the subject matter and serves as an introductory chapter. It incorporates the background of the study, problem statement, objectives of the research and a brief on the outline. Chapter 2 comprises of information relevant to this work. It includes background information on concrete characteristics, self compacting concrete, artificial intelligence, and the application of artificial neural networks in concrete research. Chapter 3 is devoted to the methodology adopted to achieve the objectives of the research. This includes investigation of the best network used for the prediction of self compacting concrete characteristics by using published experimental data. Chapter 4 describes the details on modelling and programming. It also presents all steps in designing artificial neural network and comprises the results of the main proposed training functions to obtain the best network. Chapter 5 contains the conclusions arrived at and gives the recommendations for future works. N° de réf. du vendeur 9783659199202
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