**Best Reference Books on Mathematical Modeling**, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of

**Mathematical Modeling Books**with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Mathematical Modeling below.

1."Mathematical Modeling" by J N Kapur
“Mathematical Modelling” Book Review: The field of mathematical modelling is expanding quickly and is now applied to a variety of physical, economic, and social systems. This book provides an in-depth analysis of key mathematical modelling techniques and how they can be used to solve problems in fields such as physics, chemistry, economics, demography, biology, medicine, ecology, and traffic flow. Each chapter is dedicated to a specific mathematical technique and includes numerous examples to help readers understand the concepts. The book also provides guidance on which techniques are suitable for different situations and how they can be applied in their respective fields.
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2."Mathematical Modeling" by Mark M Meerschaert
“Mathematical Modeling” Book Review: Theoretical and practical aspects of mathematical modeling are covered in this comprehensive book. Optimization models, dynamic models, and probability models are explored in detail, with MATLAB material incorporated throughout the text. The book has separate chapters dedicated to diffusion models and time series analysis. In addition, it examines the applications of mathematical modeling in genetic engineering and hurricane prediction, as well as optimization problems in whale and dolphin populations. This book is suitable for students, teachers, and professionals alike.
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3."A First Course in Mathematical Modeling" by Frank R Giordano
“A First Course in Mathematical Modeling” Book Review: This book provides a thorough introduction to the theoretical and practical aspects of modeling, covering the process of model construction, analysis, and research. It delves into topics such as differential equations as mathematical models, linear and nonlinear models, and modeling with first-order differential equations and systems of first-order differential equations. The book guides readers through a six-step problem-solving process to identify problems, construct or model them, and determine necessary data collection. This approach helps to enhance problem-solving skills. The book is a valuable resource for both students and professionals.
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4."Mathematical Modeling With Excel" by Brian Albright
“Mathematical Modeling with Excel” Book Review: The book provides an extensive range of techniques for constructing and examining mathematical models using Excel. It presents various models in a clear and concise way. At the end of each chapter, exercises are included to allow readers to modify, analyze, or adapt the existing models to comparable situations. This book is ideal for students pursuing a degree in mathematics or secondary math education.
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5."Mathematical Modelling with Case Studies: A Differential Equations Approach using Maple and MATLAB" by B Barnes and G R Fulford
“Mathematical Modelling with Case Studies: A Differential Equations Approach using Maple and MATLAB” Book Review: The focus of this book is to illustrate the application of various mathematical techniques to models that involve differential equations. The specific areas covered in this book are growth and decay processes, interactions between populations, and heating/cooling problems. The book uses flow diagrams and word equations to show the process of constructing a model and how to simplify complex problems. The book also examines the behavior of the models under varying conditions using theoretical, graphical, and computational tools, while also utilizing Maple and MATLAB for hands-on model building. The book also discusses model validation and extensions while acknowledging the advantages and disadvantages of each model presented.
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6."Mathematical Modeling: Application, Isssues and Analysis" by Viaml K Mishra
“Mathematical Modeling: Application, Issues and Analysis” Book Review: The papers included in this book are sourced from the proceedings of the National Conference on Mathematical Modeling and Analysis, covering a range of topics such as drug design, fluid mechanics, environmental pollution, applied analysis, and biological systems. The book caters to scientists, engineers, technocrats, and researchers seeking to deepen their understanding of mathematical modeling.
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7."MATHEMATICAL MODELING: MODELS, ANALYSIS AND APPLICATIONS" by SANDEEP BANERJEE
“Mathematical Modeling: Models, Analysis and Applications” Book Review: This book offers a detailed treatment of modeling using every type of differential equation. Ordinary, partial, delay, and stochastic differential equations are implemented to also explain discrete modeling. The book describes various tools and techniques for mathematical modeling and analysis to solve problems. MATLAB and Mathematica are incorporated to explain spatial, delayed, and stochastic modeling. Real-life examples as well as exercise sets on discrete and continuous mathematical modeling scenarios are also included. This book is ideal for students, engineers, and scientists in science, engineering and social sciences.
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8."Mathematical Modeling of Warfare and Combat Phenomenon" by Jeffrey Strickland
“Mathematical Modeling of Warfare and Combat Phenomenon” Book Review: This book introduces effective techniques for utilizing mathematics to solve military problems by illustrating the significance of mathematical modeling to define the interaction and connections among measurable concepts and variables. The text stresses the significance of mathematical modeling in military applications and presents models related to terrorism, search, missile defense, radar, attrition, and operational reliability. It is a valuable resource for students and professionals.
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9."Mathematical Modeling with Computer Simulation" by Daniel P Maki and Maynard Thompson
“Mathematical Modeling and Computer Simulation” Book Review: The process of building mathematical and computer models is presented dynamically in this book, which involves simplification, approximation, abstraction, analysis, computation, and comparison. The book provides numerous case studies that demonstrate how the model building process can be applied in real-life situations, such as business, genetics, population biology, and social sciences.
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10."Mathematical Modeling of Complex Biological Systems: A Kinetic Theory Approach (Modeling and Simulation in Science, Engineering and Technology)" by Abdelghani Bellouquid and Marcello Delitala
“Mathematical Modeling of Complex Biological Systems: A Kinetic Theory Approach (Modeling and Simulation in Science, Engineering and Technology)” Book Review: The book explains how mathematical theory and computer models can be used to study the development of social and biological systems. It includes a new biological model and a general equation called the Boltzmann equation. The book is useful for advanced graduate students and for people attending seminars on modeling biological systems.
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11."Mathematical Modeling, Simulation, Visualization and e-Learning" by Dialla Konaté
“Mathematical Modeling, Simulation, Visualization and e-Learning” Book Review: This is a comprehensive guide to using mathematical models and simulations for learning and problem-solving. The book covers a range of topics, including mathematical modeling, simulation, visualization, and e-learning, with an emphasis on practical applications. Konaté provides clear explanations and numerous examples to help readers develop a strong foundation in these important areas.
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12."Mathematical Modeling, Bayesian Estimation, and Inverse Problems: 3816 (Proceedings of SPIE)" by Francoise Preteux and Ali Mohammad-Djafari
“Mathematical Modeling, Bayesian Estimation, and Inverse Problems: 3816 (Proceedings of SPIE)” Book Review: This book is a collection of papers presented at the SPIE conference on Mathematical Modeling, Bayesian Estimation, and Inverse Problems. The book covers a wide range of topics related to mathematical modeling, including Bayesian estimation, inverse problems, and computational methods for solving mathematical models. The authors of the papers are experts in the field, and their contributions provide a valuable insight into the latest developments in mathematical modeling.
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