Advances in Computational Modeling and Simulation by
DOI:
https://doi.org/10.1007/978-981-16-7857-8
The book presents select proceedings of Global meet on ‘Computational Modelling and Simulation, Recent Innovations, Challenges and Perspectives, 2020. This book covers leading-edge technologies from different domains such as computation in optimization and control, multiscale and multiphysics modeling and computation analysis, environmental modeling, modeling approaches to enterprise systems and services, finite element analysis, dependability and security, high-performance computation/cloud computing applications, computational biology and chemistry and computational mechanics.
Applied Predictive Modeling by
This book provides an introduction to predictive models as well as a guide to applying them. It will serve as a useful guide for practitioners.
Bayesian Data Analysis by
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.
Bayesian Optimization: theory and practice using Python by
This book covers the essential theory and implementation of popular Bayesian optimization techniques in an intuitive and well-illustrated manner. The techniques covered in this book will enable you to better tune the hyperparemeters of your machine learning models and learn sample-efficient approaches to global optimization.
The book begins by introducing different Bayesian Optimization (BO) techniques, covering both commonly used tools and advanced topics. It follows a “develop from scratch” method using Python, and gradually builds up to more advanced libraries such as BoTorch, an open-source project introduced by Facebook recently. Along the way, you’ll see practical implementations of this important discipline along with thorough coverage and straightforward explanations of essential theories. This book intends to bridge the gap between researchers and practitioners, providing both with a comprehensive, easy-to-digest, and useful reference guide.
After completing this book, you will have a firm grasp of Bayesian optimization techniques, which you’ll be able to put into practice in your own machine learning models.
Big Practical Guide to Computer Simulations (2nd Edition) by
This book teaches you all necessary (problem-independent) tools and techniques needed to implement and perform sophisticated scientific numerical simulations. Thus, it is suited for undergraduate and graduate students who want to become experts in computer simulations in Physics, Chemistry, Biology, Engineering, Computer Science and other fields.
Body of Knowledge for Modeling and Simulation by
Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new 'Body of Knowledge' (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations. Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries--and interactions--of systems, data, and representations.
Complexity Challenges in Cyber Physical Systems by
This book provides the state-of-the-art in methods and technologies that aim to elaborate on the modeling and simulation support to CPS engineering across many sectors such as healthcare, smart grid or smart home. The book presents a compilation of simulation-based methods, technologies and approaches that encourage the reader to incorporate simulation technologies in their CPS engineering endeavors, supporting management of complexity challenges in such endeavors. There are three main elements to this: first, review of the state-of-the-art methods M&S and CPS paradigms; second, identification and/or proposition of technological support for linkages within M&S hybrid models and between M&S models and CPS structures; third, the proposition of frameworks for using M&S/CPS co-simulation for complex systems (e.g. healthcare) by way of a research roadmap.
Computational and Experimental Simulations in Engineering by
This book gathers the latest advances, innovations, and applications in the field of computational engineering, as presented by leading international researchers and engineers at the 29th International Conference on Computational & Experimental Engineering and Sciences (ICCES), held in Shenzhen, China on May 26-29, 2023. ICCES covers all aspects of applied sciences and engineering: theoretical, analytical, computational, and experimental studies and solutions of problems in the physical, chemical, biological, mechanical, electrical, and mathematical sciences. As such, the book discusses highly diverse topics, including composites; bioengineering & biomechanics; geotechnical engineering; offshore & arctic engineering; multi-scale & multi-physics fluid engineering; structural integrity & longevity; materials design & simulation; and computer modeling methods in engineering. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
A Concrete Approach to Mathematical Modelling by
With an abundance of wit and common sense, Mesterton-Gibbons shows readers exactly how the modelling process works, using fascinating real-life examples from virtually every realm of human, machine, natural, and cosmic activity.
The Elements of Statistical Learning by 
Essential Logic for Computer Science by
An introduction to applying predicate logic to testing and verification of software and digital circuits that focuses on applications rather than theory.
Computer scientists use logic for testing and verification of software and digital circuits, but many computer science students study logic only in the context of traditional mathematics, encountering the subject in a few lectures and a handful of problem sets in a discrete math course. This book offers a more substantive and rigorous approach to logic that focuses on applications in computer science. Topics covered include predicate logic, equation-based software, automated testing and theorem proving, and large-scale computation.
Fundamentals of Scientific Computing by
This overview conveys the fundamentals of mathematical models, numerical methods and algorithms. Readers will find a tutorial on the most important classes of numerical methods and an introduction to the use of spectral methods as central tools.
Handbook of Research on Computational Simulation and Modeling in Engineering by
This book is an authoritative reference source on the computer models and technologies necessary to enhance engineering structures and planning for real-world applications
Introduction to Computational Science by
Computational science is an exciting new field at the intersection of the sciences, computer science, and mathematics because much scientific investigation now involves computing as well as theory and experiment. This textbook provides students with a versatile and accessible introduction to the subject. It assumes only a background in high school algebra, enables instructors to follow tailored pathways through the material, and is the only textbook of its kind designed specifically for an introductory course in the computational science and engineering curriculum. While the text itself is generic, an accompanying website offers tutorials and files in a variety of software packages. This edition features two new chapters on agent-based simulations and modeling with matrices, ten new project modules, and an additional module on diffusion. Besides increased treatment of high-performance computing and its applications, the book also includes additional quick review questions with answers, exercises, and individual and team projects.
Introduction to MATLAB for Engineers and Scientists by
Familiarize yourself with MATLAB using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting and working with files, numerical computation formalism, and the primary concepts of approximations. Introduction to MATLAB is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.
In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts.
Introduction to Modeling and Simulation by
This new introductory-level textbook provides thirteen self-contained chapters, each covering an important topic in engineering systems modeling and simulation. The importance of such a topic cannot be overstated; modeling and simulation will only increase in importance in the future as computational resources improve and become more powerful and accessible, and as systems become more complex. This resource is a wonderful mix of practical examples, theoretical concepts, and experimental sessions that ensure a well-rounded education on the topic.
An Introduction to Stochastic Differential Equations by
Provides a quick, but very readable introduction to stochastic differential equations-that is, to differential equations subject to additive "white noise" and related random disturbances. The exposition is strongly focused upon the interplay between probabilistic intuition and mathematical rigour.
Mathematical Modeling and Computer Simulation by
Daniel Maki and Maynard Thompson provide a conceptual framework for the process of building and using mathematical models, illustrating the uses of mathematical and computer models in a variety of situations.
Mathematical Structures for Computer Science by
This new edition made the textbook the first discrete mathematics textbook to be revised in order to meet the proposed new ACM/IEEE standards of the course. It features new material, including new sections on probability, coding theory, matrices and order of magnitude.
Modeling and Design of Secure Internet of Things by
Internet of Things (IoT) devices such as sensors, wearable devices, robots, drones, and autonomous vehicles facilitate the Intelligence, Surveillance, and Reconnaissance to Command and Control and battlefield services. There are several reasons for IoT security. First, IoT devices are mass produced rapidly to be low-cost commodity items without security protection in their original design. Second, IoT devices are highly dynamic, mobile, and heterogeneous without common standards. Third, it is imperative to understand the natural world, the physical process(es) under IoT control, and how these real-world processes can be compromised before recommending any relevant security countermeasure. As a result, those systems are the frequent targets of sophisticated cyber attacks that aim to disrupt mission effectiveness.
Modeling and Simulation of Computer Networks and Systems by
Modeling and Simulation of Computer Networks and Systems: Methodologies and Applications introduces you to a broad array of modeling and simulation issues related to computer networks and systems. It focuses on the theories, tools, applications and uses of modeling and simulation in order to effectively optimize networks. It describes methodologies for modeling and simulation of new generations of wireless and mobiles networks and cloud and grid computing systems.
The Nature of Mathematical Modeling by
This is about the nature of mathematical modelling, and the kinds of techniques that are useful for modelling. It is oriented towards simple efficient implementations on computers.
Practical MATLAB Modeling with Simulink by
Employ the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs.
You’ll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.
After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering.
Princeton Companion to Applied Mathematics by
This is the most authoritative and accessible single-volume reference book on applied mathematics. Featuring numerous entries by leading experts and organized thematically, it introduces readers to applied mathematics and its uses; explains key concepts; describes important questions, laws, and functions; looks at exciting areas of research; covers modeling and simulation; explores areas of application; and more. Modeled on the popular Princeton Companion to Mathematics, this volume is an indispensable resource for undergraduate and graduate students, researchers, and practitioners in other disciplines seeking a user-friendly reference book on applied mathematics.
Simulating War: Studying Conflict Through Simulation Games by
Over the past fifty years, many thousands of conflict simulations have been published that bring the dynamics of past and possible future wars to life. In this book, Philip Sabin explores the theory and practice of conflict simulation as a topic in its own right, based on his thirty years of experience in designing wargames and using them in teaching. Simulating War sets conflict simulation in its proper context alongside more familiar techniques such as game theory and operational analysis. It explains in detail the analytical and modelling techniques involved, and it teaches you how to design your own simulations of conflicts of your choice. The book provides eight simple illustrative simulations of specific historical conflicts, complete with rules, maps and counters. Simulating War is essential reading for all recreational or professional simulation gamers, and for anyone who is interested in modelling war, from teachers and students to military officers
Simulation and Wargaming by
Based on the insights of experts in both domains, Simulation and Wargaming comprehensively explores the intersection between computer simulation and wargaming. This book shows how the practice of wargaming can be augmented and provide more detail-oriented insights using computer simulation, particularly as the complexity of military operations and the need for computational decision aids increases.