Rare event simulation using Monte Carlo methods
著者
書誌事項
Rare event simulation using Monte Carlo methods
John Wiley & Sons, 2009
大学図書館所蔵 全10件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Rare Event Simulation In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue.
Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics.
Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.
目次
Contributors. Preface.
1 Introduction to Rare Event Simulation (Gerardo Rubino and Bruno Tuffin).
PART I THEORY.
2 Importance Sampling in Rare Event Simulation (Pierre L'Ecuyer, Michel Mandjes and Bruno Tuffin).
3 Splitting Techniques (Pierre L'Ecuyer, Francois Le Gland, Pascal Lezaud and Bruno Tuffin).
4 Robustness Properties and Confidence Interval Reliability Issues (Peter W. Glynn, Gerardo Rubino and Bruno Tuffin).
PART II APPLICATIONS.
5 Rare Event Simulation for Queues (Jose Blanchet and Michel Mandjes).
6 Markovian Models for Dependability Analysis (Gerardo Rubino and Bruno Tuffin).
7 Rare Event Analysis by Monte Carlo Techniques in Static Models (Hector Cancela, Mohamed El Khadiri and Gerardo Rubino).
8 Rare Event Simulation and Counting Problems (Jose Blanchet and Daniel Rudoy).
9 Rare Event Estimation for a Large-Scale Stochastic Hybrid System with Air Traffic Application (Henk A. P. Blom, G. J. (Bert) Bakker and Jaroslav Krystul).
10 Particle Transport Applications (Thomas Booth).
11 Rare Event Simulation Methodologies in Systems Biology (Werner Sandmann).
Index.
「Nielsen BookData」 より