Mathematical Modeling And Optimization For Real Life Phenomena PDF Download
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Author | : Cristiana J. Silva |
Publisher | : Frontiers Media SA |
Total Pages | : 135 |
Release | : 2024-03-13 |
Genre | : Science |
ISBN | : 2832546064 |
Download Mathematical modeling and optimization for real life phenomena Book in PDF, ePub and Kindle
Mathematical modeling of real life phenomena is a powerful tool in analyzing and describing their dynamical behavior. These models can be optimized and controlled using appropriate optimization methods and optimal control theory. Different characterization techniques are used to explain a real natural phenomenon by numerical simulations or experimental approximations.
Author | : J. A. Tenreiro Machado |
Publisher | : Springer Nature |
Total Pages | : 204 |
Release | : 2020-02-12 |
Genre | : Mathematics |
ISBN | : 3030370623 |
Download Mathematical Modelling and Optimization of Engineering Problems Book in PDF, ePub and Kindle
This book presents recent developments in modelling and optimization of engineering systems and the use of advanced mathematical methods for solving complex real-world problems. It provides recent theoretical developments and new techniques based on control, optimization theory, mathematical modeling and fractional calculus that can be used to model and understand complex behavior in natural phenomena including latest technologies such as additive manufacturing. Specific topics covered in detail include combinatorial optimization, flow and heat transfer, mathematical modelling, energy storage and management policy, artificial intelligence, optimal control, modelling and optimization of manufacturing systems.
Author | : Solym Mawaki Manou-Abi |
Publisher | : John Wiley & Sons |
Total Pages | : 308 |
Release | : 2020-04-28 |
Genre | : Mathematics |
ISBN | : 1786304546 |
Download Mathematical Modeling of Random and Deterministic Phenomena Book in PDF, ePub and Kindle
This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.
Author | : Ivan V. Sergienko |
Publisher | : Springer |
Total Pages | : 341 |
Release | : 2014-12-11 |
Genre | : Mathematics |
ISBN | : 1489975446 |
Download Optimization Models in a Transition Economy Book in PDF, ePub and Kindle
This book opens new avenues in understanding mathematical models within the context of a transition economy. The exposition lays out the methods for combining different mathematical structures and tools to effectively build the next model that will accurately reflect real world economic processes. Mathematical modeling of weather phenomena allows us to forecast certain essential weather parameters without any possibility of changing them. By contrast, modeling of transition economies gives us the freedom to not only predict changes in important indexes of all types of economies, but also to influence them more effectively in the desired direction. Simply put: any economy, including a transitional one, can be controlled. This book is useful to anyone who wants to increase profits within their business, or improve the quality of their family life and the economic area they live in. It is beneficial for undergraduate and graduate students specializing in the fields of Economic Informatics, Economic Cybernetics, Applied Mathematics and Large Information Systems, as well as for professional economists, and employees of state planning and statistical organizations.
Author | : Tony Hürlimann |
Publisher | : Springer Science & Business Media |
Total Pages | : 323 |
Release | : 2013-03-14 |
Genre | : Mathematics |
ISBN | : 147575793X |
Download Mathematical Modeling and Optimization Book in PDF, ePub and Kindle
Computer-based mathematical modeling - the technique of representing and managing models in machine-readable form - is still in its infancy despite the many powerful mathematical software packages already available which can solve astonishingly complex and large models. On the one hand, using mathematical and logical notation, we can formulate models which cannot be solved by any computer in reasonable time - or which cannot even be solved by any method. On the other hand, we can solve certain classes of much larger models than we can practically handle and manipulate without heavy programming. This is especially true in operations research where it is common to solve models with many thousands of variables. Even today, there are no general modeling tools that accompany the whole modeling process from start to finish, that is to say, from model creation to report writing. This book proposes a framework for computer-based modeling. More precisely, it puts forward a modeling language as a kernel representation for mathematical models. It presents a general specification for modeling tools. The book does not expose any solution methods or algorithms which may be useful in solving models, neither is it a treatise on how to build them. No help is intended here for the modeler by giving practical modeling exercises, although several models will be presented in order to illustrate the framework. Nevertheless, a short introduction to the modeling process is given in order to expound the necessary background for the proposed modeling framework.
Author | : N.V. Hritonenko |
Publisher | : Springer Science & Business Media |
Total Pages | : 307 |
Release | : 2013-04-17 |
Genre | : Mathematics |
ISBN | : 1441991603 |
Download Applied Mathematical Modelling of Engineering Problems Book in PDF, ePub and Kindle
The subject of the book is the "know-how" of applied mathematical modelling: how to construct specific models and adjust them to a new engineering environment or more precise realistic assumptions; how to analyze models for the purpose of investigating real life phenomena; and how the models can extend our knowledge about a specific engineering process. Two major sources of the book are the stock of classic models and the authors' wide experience in the field. The book provides a theoretical background to guide the development of practical models and their investigation. It considers general modelling techniques, explains basic underlying physical laws and shows how to transform them into a set of mathematical equations. The emphasis is placed on common features of the modelling process in various applications as well as on complications and generalizations of models. The book covers a variety of applications: mechanical, acoustical, physical and electrical, water transportation and contamination processes; bioengineering and population control; production systems and technical equipment renovation. Mathematical tools include partial and ordinary differential equations, difference and integral equations, the calculus of variations, optimal control, bifurcation methods, and related subjects.
Author | : J. A. Tenreiro Machado |
Publisher | : Springer Nature |
Total Pages | : 231 |
Release | : 2020-02-19 |
Genre | : Mathematics |
ISBN | : 3030371417 |
Download Numerical Solutions of Realistic Nonlinear Phenomena Book in PDF, ePub and Kindle
This collection covers new aspects of numerical methods in applied mathematics, engineering, and health sciences. It provides recent theoretical developments and new techniques based on optimization theory, partial differential equations (PDEs), mathematical modeling and fractional calculus that can be used to model and understand complex behavior in natural phenomena. Specific topics covered in detail include new numerical methods for nonlinear partial differential equations, global optimization, unconstrained optimization, detection of HIV- Protease, modelling with new fractional operators, analysis of biological models, and stochastic modelling.
Author | : Josef Kallrath |
Publisher | : Springer Science & Business Media |
Total Pages | : 427 |
Release | : 2013-12-01 |
Genre | : Mathematics |
ISBN | : 1461302153 |
Download Modeling Languages in Mathematical Optimization Book in PDF, ePub and Kindle
This volume presents a unique combination of modeling and solving real world optimization problems. It is the only book which treats systematically the major modeling languages and systems used to solve mathematical optimization problems, and it also provides a useful overview and orientation of today's modeling languages in mathematical optimization. It demonstrates the strengths and characteristic features of such languages and provides a bridge for researchers, practitioners and students into a new world: solving real optimization problems with the most advances modeling systems.
Author | : Ewald Lindner |
Publisher | : Springer Nature |
Total Pages | : 165 |
Release | : 2020-12-05 |
Genre | : Mathematics |
ISBN | : 3030503887 |
Download Mathematical Modelling in Real Life Problems Book in PDF, ePub and Kindle
This book is intended to be a useful contribution for the modern teaching of applied mathematics, educating Industrial Mathematicians that will meet the growing demand for such experts. It covers many applications where mathematics play a fundamental role, from biology, telecommunications, medicine, physics, finance and industry. It is presented in such a way that can be useful in Modelation, Simulation and Optimization courses, targeting master and PhD students. Its content is based on many editions from the successful series of Modelling Weeks organized by the European Consortium of Mathematics in Industry (ECMI). Each chapter addresses a particular problem, and is written in a didactic way, providing the description of the problem, the particular way of approaching it and the proposed solution, along with the results obtained.
Author | : Klaus Schittkowski |
Publisher | : Springer Science & Business Media |
Total Pages | : 406 |
Release | : 2013-06-05 |
Genre | : Computers |
ISBN | : 1441957626 |
Download Numerical Data Fitting in Dynamical Systems Book in PDF, ePub and Kindle
Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.