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portada Composite Materials Technology: Neural Network Applications (en Inglés)
Formato
Libro Físico
Editorial
Idioma
Inglés
N° páginas
368
Encuadernación
Tapa Dura
Dimensiones
23.6 x 15.5 x 2.0 cm
Peso
0.66 kg.
ISBN
9781420093322
ISBN13
9781420093322

Composite Materials Technology: Neural Network Applications (en Inglés)

Sapuan, S. M. ; Mujtaba, Iqbal Mohammed (Autor) · CRC Press · Tapa Dura

Composite Materials Technology: Neural Network Applications (en Inglés) - Sapuan, S. M. ; Mujtaba, Iqbal Mohammed

Libro Físico

$ 189.790

$ 379.570

Ahorras: $ 189.780

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Origen: Reino Unido (Costos de importación incluídos en el precio)
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Reseña del libro "Composite Materials Technology: Neural Network Applications (en Inglés)"

Artificial neural networks (ANN) can provide new insight into the study of composite materials and can normally be combined with other artificial intelligence tools such as expert system, genetic algorithm, and fuzzy logic. Because research on this field is very new, there is only a limited amount of published literature on the subject.Compiling information from diverse sources, Composite Materials Technology: Neural Network Applications fills the void in knowledge of these important networks, covering composite mechanics, materials characterization, product design, and other important aspects of polymer matrix composites.Light weight, corrosion resistance, good stiffness and strength properties, and part consolidation are just some of the reasons that composites are useful in areas including civil engineering and structure, chemical processing, management, agriculture, space study, and manufacturing. ANN has already been used to carry out design prediction, mechanical property prediction, and selection processes in the evolution of composites, but although it has already been used with great success in various branches of scientific and technological research, it is still in the nascent stage of its development.Featuring contributions from leading researchers throughout the world, this book is divided into four parts, starting with an introduction to neural networks and a review of existing literature on the subject. The text then covers structural health monitoring and damage detection in composites, addresses mechanical properties, and discusses design, analysis, and materials selection. Training, testing, and validation of experimental data were carried out to optimize the results presented in the book.This book will be an important aid to researchers as they work on the future implementation of ANN in industries such as aerospace, automotive, marine, sporting goods, furniture, and electronics and communication.

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