Open access peer-reviewed Edited Volume

The Monte Carlo Methods - Recent Advances, New Perspectives and Applications

Abdo Abou Jaoude

Notre Dame University - Louaize

A pioneering researcher in pure and applied mathematics, computer science, and prognostics, holder of multiple PhDs in Applied Mathematics, Computer Science, Applied Statistics and Probability and two PhDs in Mathematics and Prognostics from the Lebanese University, Lebanon, and from Aix-Marseille University, France.


Computers Coding Forecasting Models Probability Theory Random Phenomena Applications Simulations Stochastic Problems Engineering Problems Scientific Phenomena

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About the book

In applied mathematics, the name Monte Carlo is given to the method of solving problems by means of experiments with random numbers. This name, after the casino at Monaco, was first applied around 1944 to the method of solving deterministic problems by reformulating them in terms of a problem with random elements which could then be solved by large-scale sampling. But, by extension, the term has come to mean any simulation that uses random numbers.

The development and proliferation of computers have led to the widespread use of Monte Carlo methods in virtually all branches of science, ranging from nuclear physics (where computer-aided Monte Carlo was first applied) to astrophysics, biology, engineering, medicine, operations research, and the social sciences.

The Monte Carlo Method of solving problems by using random numbers in a computer – either by direct stimulation of physical or statistical problems or by reformulating deterministic problems in terms of one incorporating randomness – has become one of the most important tools of applied mathematics and computer science. A significant proportion of articles in technical journals in such fields as physics, chemistry, and statistics contain articles reporting results of Monte Carlo simulations or suggestions on how they might be applied. Some journals are devoted almost entirely to Monte Carlo problems in their fields. Studies in the formation of the universe or of stars and their planetary systems use Monte Carlo techniques. Studies in genetics, the biochemistry of DNA, and the random configuration and knotting of biological molecules are studied by Monte Carlo methods. In number theory, Monte Carlo methods play an important role in determining primality or factoring of very large integers far beyond the range of deterministic methods. Several important new statistical techniques such as “bootstrapping” and “jackknifing” are based on Monte Carlo methods.

Hence, the role of Monte Carlo methods and simulation in all of the sciences has increased in importance during the past several years. These methods play a central role in the rapidly developing subdisciplines of the computational physical sciences, the computational life sciences, and the other computational sciences. Therefore, the growing power of computers and the evolving simulation methodology have led to the recognition of computation as a third approach for advancing the natural sciences, together with theory and traditional experimentation. Additionally, at the kernel of Monte Carlo simulation is random number generation.

Finally, the aims of the current book are to discuss the Monte Carlo methods and techniques applied in mathematics in particular and in various and diverse scientific problems in general.

Publishing process

Book initiated and editor appointed

Date completed: April 21st 2021

Applications to edit the book are assessed and a suitable editor is selected, at which point the process begins.

Chapter proposals submitted and reviewed

Deadline for chapter proposals: May 19th 2021

Potential authors submit chapter proposals ready for review by the academic editor and our publishing review team.

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Approved chapters written in full and submitted

Deadline for full chapters: July 18th 2021

Once approved by the academic editor and publishing review team, chapters are written and submitted according to pre-agreed parameters

Full chapters peer reviewed

Review results due: October 6th 2021

Full chapter manuscripts are screened for plagiarism and undergo a Main Editor Peer Review. Results are sent to authors within 30 days of submission, with suggestions for rounds of revisions.

Book compiled, published and promoted

Expected publication date: December 5th 2021

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About the editor

Abdo Abou Jaoude

Notre Dame University - Louaize

Abdo Abou Jaoudé has been teaching for many years and has a passion for researching and teaching mathematics. He is currently Associate Professor of Mathematics and Statistics at Notre Dame University-Louaizé (NDU), Lebanon. He holds a BSc and an MSc in Computer Science from NDU, and three PhDs in Applied Mathematics, Computer Science, and Applied Statistics and Probability, all completed at Bircham International University through a distance learning program. He also holds two PhDs in Mathematics and Prognostics from the Lebanese University, Lebanon, and from Aix-Marseille University, France. Dr. Abou Jaoudé’s broad research interests are in the field of applied mathematics, and he has published twenty-three international journal articles and six contributions to conference proceedings, in addition to five books on prognostics, applied mathematics, and computer science.

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Book chapters authored 2

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