Isbn: 9781599040998 - intelligent computational paradigms in earthquake engineering (10 risultati)

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Condizione: New. Print on Demand pp. 464 68:B&W 7 x 10 in or 254 x 178 mm Case Laminate on White w/Gloss Lam.

Condizione: New. Print on Demand pp. 464.

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Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Covers real-world engineering problems, and explores the implementation of neural networks for the representation of structural responses in earthquake engineering. This book assesses the efficiency of seismic design procedures and describes the findings in.…

Buch. Condizione: Neu. Intelligent Computational Paradigms in Earthquake Engineering | Nikos D. Lagaros | Buch | Gebunden | Englisch | 2006 | Idea Group Publishing | EAN 9781599040998 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The enormous advances in computational hardware and software resources over the last fifteen years resulted in the development of non-conventional data processing and simulation methods. Among these methods artificial intelligence (AI) has been mentioned as one of the most eminent approaches to the so-called intelligent methods of information processing that present a great potential for engineering applications. Intelligent Computational Paradigms in Earthquake Engineering contains contributions that cover a wide spectrum of very important real-world engineering problems, and explore the implementation of neural networks for the representation of structural responses in earthquake engineering. This book assesses the efficiency of seismic design procedures and describes the latest findings in intelligent optimal control systems and their applications in structural engineering. Intelligent Computational Paradigms in Earthquake Engineering presents the application of learning machines, artificial neural networks and support vector machines as highly-efficient pattern recognition tools for structural damage detection. principles that considers seismic risk, and emphasizes the use of AI methodologies in a geotechnical earthquake engineering application.…