Alan Stevens – författare

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.

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.

STEM Problems with Mathcad and Python seeks to remove the fear of tackling difficult scientific and technical calculations for future mathematicians, engineers, scientists, and other STEM researchers. The authors hope to show that such calculations can be not only useful, but that the process of learning how to do them can be enjoyable, especially with the help of Mathcad and Python programming skills. The book will also illustrate how the use of modern computer software allows one to significantly expand the range of problems considered beyond those conventionally taught. This includes computational experiments, multivariate calculations, inverse problems and optimization problems, with both static and animated visual feedback.

Features

STEM Problems with Mathcad and Python seeks to remove the fear of tackling difficult scientific and technical calculations for future mathematicians, engineers, scientists, and other STEM researchers. The authors hope to show that such calculations can be not only useful, but that the process of learning how to do them can be enjoyable, especially with the help of Mathcad and Python programming skills. The book will also illustrate how the use of modern computer software allows one to significantly expand the range of problems considered beyond those conventionally taught. This includes computational experiments, multivariate calculations, inverse problems and optimization problems, with both static and animated visual feedback.

Features