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- Author: Alan Stevens
- Publisher: CRC Press
- ISBN-10: 1032280778
- ISBN-13: 9781032280776
- Format: 15.6 x 23.4 x 0.8 cm, kieti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
Monte-Carlo techniques have increasingly become a key method used in quantitative research. This book introduces engineers and scientists to the basics of using the Monte-Carlo simulation method which is used in Operations Research and other fields to understand the impact of risk and uncertainty in prediction and forecasting models.
Monte-Carlo Simulation: An Introduction for Engineers and Scientists explores several specific applications in addition to illustrating the principles behind the methods. The question of accuracy and efficiency with using the method is addressed thoroughly within each chapter and all program listings are included in the discussion of each application to facilitate further research for the reader using Python programming language.
Beginning engineers and scientists either already in or about to go into industry or commercial and government scientific laboratories will find this book essential. It could also be of interest to undergraduates in engineering science and mathematics, as well as instructors and lecturers who have no prior knowledge of Monte-Carlo simulations.
EXTRA 10 % discount with code: EXTRA
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- Author: Alan Stevens
- Publisher: CRC Press
- ISBN-10: 1032280778
- ISBN-13: 9781032280776
- Format: 15.6 x 23.4 x 0.8 cm, kieti viršeliai
- Language: English English
Monte-Carlo techniques have increasingly become a key method used in quantitative research. This book introduces engineers and scientists to the basics of using the Monte-Carlo simulation method which is used in Operations Research and other fields to understand the impact of risk and uncertainty in prediction and forecasting models.
Monte-Carlo Simulation: An Introduction for Engineers and Scientists explores several specific applications in addition to illustrating the principles behind the methods. The question of accuracy and efficiency with using the method is addressed thoroughly within each chapter and all program listings are included in the discussion of each application to facilitate further research for the reader using Python programming language.
Beginning engineers and scientists either already in or about to go into industry or commercial and government scientific laboratories will find this book essential. It could also be of interest to undergraduates in engineering science and mathematics, as well as instructors and lecturers who have no prior knowledge of Monte-Carlo simulations.
Reviews