Engineering risk assessment with subset simulation /

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Au, Siu-Kui
Άλλοι συγγραφείς: Wang, Yu, 1977-
Μορφή: Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Wiley, 2014.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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049 |a MAIN 
100 1 |a Au, Siu-Kui. 
245 1 0 |a Engineering risk assessment with subset simulation /  |c Siu-Kui Au, Yu Wang. 
264 1 |a Singapore :  |b Wiley,  |c 2014. 
300 |a 1 online resource (337 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
588 0 |a Print version record. 
504 |a Includes bibliographical references and index. 
520 |a 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 th. 
650 0 |a Engineering design  |x Mathematics. 
650 0 |a Risk assessment  |x Mathematics. 
650 4 |a Engineering design  |x Mathematics. 
650 4 |a Risk assessment  |x Mathematics. 
650 4 |a Set theory. 
655 4 |a Electronic books. 
700 1 |a Wang, Yu,  |d 1977- 
776 0 8 |i Print version:  |a Au, Siu-Kui.  |t Engineering Risk Assessment with Subset Simulation.  |d Hoboken : Wiley, ©2014  |z 9781118398043 
856 4 0 |u https://doi.org/10.1002/9781118398050  |z Full Text via HEAL-Link 
994 |a 92  |b DG1