Deterministic and Stochastic Approaches in Computer Modeling and Simulation

Deterministic and Stochastic Approaches in Computer Modeling and Simulation
Author :
Publisher : IGI Global
Total Pages : 527
Release :
ISBN-10 : 9781668489499
ISBN-13 : 166848949X
Rating : 4/5 (49X Downloads)

Book Synopsis Deterministic and Stochastic Approaches in Computer Modeling and Simulation by : Romansky, Radi Petrov

Download or read book Deterministic and Stochastic Approaches in Computer Modeling and Simulation written by Romansky, Radi Petrov and published by IGI Global. This book was released on 2023-10-09 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the field of computer modeling and simulation, academic scholars face a pressing challenge—how to navigate the complex landscape of both deterministic and stochastic approaches to modeling. This multifaceted arena demands a unified organizational framework, a comprehensive guide that can seamlessly bridge the gap between theory and practical application. Without such a resource, scholars may struggle to harness the full potential of computer modeling, leaving critical questions unanswered and innovative solutions undiscovered. Deterministic and Stochastic Approaches in Computer Modeling and Simulation serves as the definitive solution to the complex problem scholars encounter. By presenting a comprehensive and unified organizational approach, this book empowers academics to conquer the challenges of computer modeling with confidence. It not only provides a classification of modeling methods but also offers a formalized, step-by-step approach to conducting model investigations, starting from defining objectives to analyzing experimental results. For academic scholars seeking a holistic understanding of computer modeling, this book is the ultimate solution. It caters to the diverse needs of scholars by addressing both deterministic and stochastic approaches. Through its structured chapters, it guides readers from the very basics of computer systems investigation to advanced topics like stochastic analytical modeling and statistical modeling.


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