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Añadir al carritoCondición: Very Good. Auflage: 2014.
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Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2014
ISBN 10: 1118398041 ISBN 13: 9781118398043
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 153,62
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Añadir al carritoHardback. Condición: New. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. It then introduces a class of powerful simulation techniques called Markov Chain Monte Carlo method (MCMC), an important machinery behind Subset Simulation that allows one to generate samples for investigating rare scenarios in a probabilistically consistent manner. The theory of Subset Simulation is then presented, addressing related practical issues encountered in the actual implementation. The book also introduces the reader to probabilistic failure analysis and reliability-based sensitivity analysis, which are laid out in a context that can be efficiently tackled with Subset Simulation or Monte Carlo simulation in general. The book is supplemented with an Excel VBA code that provides a user-friendly tool for the reader to gain hands-on experience with Monte Carlo simulation. Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity analysisIllustrates examples with MS Excel spreadsheets, allowing readers to gain hands-on experience with Monte Carlo simulationCovers theoretical fundamentals as well as advanced implementation issuesA companion website is available to include the developments of the software ideas This book is essential reading for graduate students, researchers and engineers interested in applying Monte Carlo methods for risk assessment and reliability based design in various fields such as civil engineering, mechanical engineering, aerospace engineering, electrical engineering and nuclear engineering. Project managers, risk managers and financial engineers dealing with uncertainty effects may also find it useful.
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EUR 130,65
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Añadir al carritoCondición: New. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications.Klappentext.
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Añadir al carritoHardcover. Condición: Like New. Like New. book.
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Añadir al carritoHardcover. Condición: Brand New. 1st edition. 300 pages. 10.00x7.00x1.00 inches. In Stock.
Idioma: Inglés
Publicado por John Wiley and Sons Inc, US, 2014
ISBN 10: 1118398041 ISBN 13: 9781118398043
Librería: Rarewaves.com UK, London, Reino Unido
EUR 144,81
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Añadir al carritoHardback. Condición: New. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. It then introduces a class of powerful simulation techniques called Markov Chain Monte Carlo method (MCMC), an important machinery behind Subset Simulation that allows one to generate samples for investigating rare scenarios in a probabilistically consistent manner. The theory of Subset Simulation is then presented, addressing related practical issues encountered in the actual implementation. The book also introduces the reader to probabilistic failure analysis and reliability-based sensitivity analysis, which are laid out in a context that can be efficiently tackled with Subset Simulation or Monte Carlo simulation in general. The book is supplemented with an Excel VBA code that provides a user-friendly tool for the reader to gain hands-on experience with Monte Carlo simulation. Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity analysisIllustrates examples with MS Excel spreadsheets, allowing readers to gain hands-on experience with Monte Carlo simulationCovers theoretical fundamentals as well as advanced implementation issuesA companion website is available to include the developments of the software ideas This book is essential reading for graduate students, researchers and engineers interested in applying Monte Carlo methods for risk assessment and reliability based design in various fields such as civil engineering, mechanical engineering, aerospace engineering, electrical engineering and nuclear engineering. Project managers, risk managers and financial engineers dealing with uncertainty effects may also find it useful.
EUR 161,32
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Añadir al carritoBuch. Condición: Neu. Neuware - This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. It then introduces a class of powerful simulation techniques called Markov Chain Monte Carlo method (MCMC), an important machinery behind Subset Simulation that allows one to generate samples for investigating rare scenarios in a probabilistically consistent manner. The theory of Subset Simulation is then presented, addressing related practical issues encountered in the actual implementation. The book also introduces the reader to probabilistic failure analysis and reliability-based sensitivity analysis, which are laid out in a context that can be efficiently tackled with Subset Simulation or Monte Carlo simulation in general. The book is supplemented with an Excel VBA code that provides a user-friendly tool for the reader to gain hands-on experience with Monte Carlo simulation. - Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity analysis - Illustrates examples with MS Excel spreadsheets, allowing readers to gain hands-on experience with Monte Carlo simulation - Covers theoretical fundamentals as well as advanced implementation issues - A companion website is available to include the developments of the software ideas This book is essential reading for graduate students, researchers and engineers interested in applying Monte Carlo methods for risk assessment and reliability based design in various fields such as civil engineering, mechanical engineering, aerospace engineering, electrical engineering and nuclear engineering. Project managers, risk managers and financial engineers dealing with uncertainty effects may also find it useful.
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 230,97
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Añadir al carritoCondición: New. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. Num Pages: 300 pages, illustrations. BIC Classification: PBW; TGPR. Category: (P) Professional & Vocational. Dimension: 257 x 179 x 21. Weight in Grams: 670. . 2014. 1st Edition. hardcover. . . . . Books ship from the US and Ireland.
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Original o primera edición
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Añadir al carritoCondición: New. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. Num Pages: 300 pages, illustrations. BIC Classification: PBW; TGPR. Category: (P) Professional & Vocational. Dimension: 257 x 179 x 21. Weight in Grams: 670. . 2014. 1st Edition. hardcover. . . . .
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Añadir al carritoCondición: gut. Engineering Risk C In englischer Sprache. pages.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por John Wiley & Sons Inc, New York, 2014
ISBN 10: 1118398041 ISBN 13: 9781118398043
Librería: CitiRetail, Stevenage, Reino Unido
Original o primera edición Impresión bajo demanda
EUR 128,02
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Añadir al carritoHardcover. Condición: new. Hardcover. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. It then introduces a class of powerful simulation techniques called Markov Chain Monte Carlo method (MCMC), an important machinery behind Subset Simulation that allows one to generate samples for investigating rare scenarios in a probabilistically consistent manner. The theory of Subset Simulation is then presented, addressing related practical issues encountered in the actual implementation. The book also introduces the reader to probabilistic failure analysis and reliability-based sensitivity analysis, which are laid out in a context that can be efficiently tackled with Subset Simulation or Monte Carlo simulation in general. The book is supplemented with an Excel VBA code that provides a user-friendly tool for the reader to gain hands-on experience with Monte Carlo simulation. Presents a powerful simulation method called Subset Simulation for efficient engineering risk assessment and failure and sensitivity analysisIllustrates examples with MS Excel spreadsheets, allowing readers to gain hands-on experience with Monte Carlo simulationCovers theoretical fundamentals as well as advanced implementation issuesA companion website is available to include the developments of the software ideas This book is essential reading for graduate students, researchers and engineers interested in applying Monte Carlo methods for risk assessment and reliability based design in various fields such as civil engineering, mechanical engineering, aerospace engineering, electrical engineering and nuclear engineering. Project managers, risk managers and financial engineers dealing with uncertainty effects may also find it useful. This book starts with the basic ideas in uncertainty propagation using Monte Carlo methods and the generation of random variables and stochastic processes for some common distributions encountered in engineering applications. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.