الصفحة 5
الصفحة 5
Modellistica numerica per problemi differenziali = Numerical modeling for differential problems
This text introduces the basic concepts for the numerical modeling of partial differential problems. We consider the classic elliptic, parabolic and hyperbolic linear equations, but also other equations, such as those of diffusion and transport, of Navier-Stokes, and the conservation laws, and we provide numerous physical examples underlying these equations. Then we analyze numerical resolution methods based on finite elements, finite differences, finite volumes, spectral methods and domain decomposition methods. In particular, the algorithmic and computer implementation aspects are discussed and various easy-to-use programs are provided.
Modellistica Numerica per Problemi Differenziali = Numerical Modeling for Differential Problems
This text introduces the fundamental concepts for the numerical modeling of partial differential problems. We consider the classic linear elliptic, parabolic and hyperbolic equations, but also other equations, such as those of diffusion and transport, of Navier-Stokes, and the conservation laws. Numerous physical examples underlying these equations are provided, their main mathematical properties are studied, then numerical resolution methods based on finite elements, finite differences, finite volumes and spectral methods are proposed and analyzed. In particular, the algorithmic and computer implementation aspects are discussed and some easy-to-use programs in C ++ language are provided. The text does not presuppose an advanced mathematical knowledge of partial differential equations: the strictly indispensable concepts in this regard are reported in the Appendix. The volume is therefore suitable for students of scientific degree courses (Engineering, Mathematics, Physics, Chemistry, Information Sciences) and recommended for researchers from the academic and extra-academic world who want to approach this interesting branch of applied mathematics.
Modelling, Computation and Optimization in Information Systems and Management Sciences ; 2nd International Conference MCO 2008, Metz, France - Luxembourg, September 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference MCO 2008, Metz, France, September 2008.The 65 revised full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on optimization and decision making; data mining theory, systems and applications; computer vision and image processing; computer communications and networks; optimization and search techniques for security, reliability, trust.
Modelling, Analysis and Optimization of Biosystems
Mathematical models in biology and medicine cannot be based on natural laws as it is the case with physics and chemistry. This is due to the fact that biological and medical processes are concerned with living organisms. Mathematical models, however, can be used as a language by which certain aspects of biological or medical processes can be expressed. In general, several mathematical models can be designed in order to describe a biological or medical process and there is no unique criterion which model gives the best description. This book presents several of these models and shows applications of them to different biological and medical problems. The book shows that operations research expertise is necessary in respect to modeling, analysis and optimization of biosystems.
Modelling the dispersion of radionuclides in the marine environment : An introduction
This book is a practical guide to the subject of numerical modelling of radioactivity dispersion in the marine environment. Thus, the techniques and numerical procedures required are explained in detail, with the aim of enabling the reader to build a real mathematical model. The book covers basic concepts and techniques, such as solving the advection-diffusion equation in a simple 1D form, as well as the most recent developments (full 3D models for non-conservative radionuclides including chemical reactions and speciation). A chapter is dedicated to the basic hydrodynamic modelling that is always required to simulate the dispersion of tracers in the sea; Eulerian and Lagrangian modelling techniques are also described. A chapter describes sensitivity and uncertainty analysis, the final stage in modelling works. A review on some published radionuclide dispersion models is also included.
Modelling in Mathematical Programming : Methodology and Techniques
This book provides basic tools for learning how to model in mathematical programming, from models without much complexity to complex system models. It presents a unique methodology for the building of an integral mathematical model, as well as new techniques that help build under own criteria. It allows readers to structure models from the elements and variables to the constraints, a basic modelling guide for any system with a new scheme of variables, a classification of constraints and also a set of rules to model specifications stated as logical propositions, helping to better understand models already existing in the literature. It also presents the modelling of all possible objectives that may arise in optimization problems regarding the variables values. The book is structured to guide the reader in an orderly manner, learning of the components that the methodology establishes in an optimization problem. The system includes the elements, which are all the actors that participate in the system, decision activities that occur in the system, calculations based on the decision activities, specifications such as regulations, impositions or actions of defined value and objective criterion, which guides the resolution of the system.
Modelli Matematici in Biologia = Mathematical Models in Biology
This text is addressed first of all to the students of the Specialist Degrees in Biology of the Universities, but it will also be of interest to students of Natural Sciences and Medicine. The topics covered include the most classic mathematical models of biological phenomena (population dynamics, spread of infectious diseases, simple physiology models), but a relevant part of the text is dedicated to the mathematical approach to the theory of natural evolution. The only prerequisites required of the reader are those provided by the basic courses of Mathematics of the Bachelor's Degree in Biology, Natural Sciences or Medicine.
Modelli Dinamici Discreti = Discrete Dynamic Models
Discrete mathematical modeling is one of the driving factors in modern mathematics research, and has played a role of synthesis between different disciplines, becoming a tool for qualitative and quantitative analysis in applied sciences. This volume provides an introduction to the analysis of discrete dynamic systems, following a modeling approach. An examination of a wide range of examples, models, and motivations drawn from Biology, Demography, Engineering and Economics, is followed by the presentation of the tools for the study of linear and non-linear scalar dynamical systems, with particular attention to stability analysis. The linear difference equations are studied in detail and an elementary introduction to the Z and DFT transforms is provided. One chapter is devoted to the study of bifurcations and chaotic dynamics. One-step vector dynamical systems and the applications of Markov chains are the subject of three chapters.
Modélisation et statistique spatiales = Spatial modeling and statistics
Spatial statistics are undergoing significant development due to their use in many fields: earth sciences, environment and climatology, epidemiology, econometrics, image analysis, etc. This book presents the main spatial models used as well as their statistics for the three types of data: geostatistics (observation on a continuous domain), data on a discrete network, point data. The objective is to present in a concise but mathematically complete way the most classical models (second order and variogram; software model and Gibbs-Markov field; point processes) as well as their simulation by MCMC algorithm. Then comes the presentation of statistical tools useful for their study.
Modeling, Simulation and Optimization of Complex Processes HPSC 2018 ; Proceedings of the 7th International Conference on High Performance Scientific Computing, Hanoi, Vietnam, March 19-23, 2018
The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the Third International Conference on High Performance Scientific Computing, March 6–10, 2006, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the Third International Conference on High Performance Scientific Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, and its International PhD Program ``Complex Processes: Modeling, Simulation and Optimization'', and Ho Chi Minh City University of Technology. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and control, parallel computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the International Conference on High Performance Scientific Computing, March 10-14, 2003, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the symposium "International Conference on High Performance Scientific Computing'' held at the Hanoi Institute of Mathematics of the Vietnam National Center for Natural Science and Technology (NCST). The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and optimal control, parallel computing, symbolic computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
Modeling, Estimation and Control : Festschrift in Honor of Giorgio Picci on the Occasion of his Sixty-Fifth Birthday
Coefficients of Variations in Analysis of Macro-Policy Effects: An example of two-parameter Poisson-Dirichlet distributions.- How Many Experiments Are Needed to Adapt?- A Mutual Information Based Distance for Multivariate Gaussian Processes.- Differential Forms and Dynamical Systems.- An Algebraic Framework for Bayes Nets of Time Series.- A Birds Eye View on System Identification.- Further Results on the Byrnes-Georgiou-Lindquist Generalized Moment Problem.- Factor Analysis and Alternating Minimization.- Tensored PolynomialModels.- Distances Between Time-Series and Their Autocorrelation Statistics.- Global Identifiability of Complex Models, Constructed from Simple Submodels.- Identification of Hidden MarkovModels - Uniform LLN-s.- Identifiability and Informative Experiments in Open and Closed-Loop Identification.- On Interpolation and the Kimura-Georgiou Parametrization.- The Control of Error in Numerical Methods.- Contour Reconstruction and Matching Using Recursive Smoothing Splines.- Role of LQ Decomposition in Subspace Identification Methods.- Canonical Operators on Graphs.
Modeling Uncertainty : An Examination of Stochastic Theory, Methods, and Applications
Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum.
Modeling of Soft Matter
Soft matter plays a role in a wide variety of important processes and application. For example, gel swelling and dynamics are an essential part of many biological and individual processes, such as motility mechanisms in bacteria and the transport and absorption of drugs. Ferroelectrics, liquid crystals, and elastomers are being used to design ever faster switching devices. Experimental studies, such as scattering, optical and electron microscopy, have provided a great deal of detailed information on structures. But the integration of mathematical modeling and analysis with experimental approaches promises to greatly increase our understanding of structure-property relationships and constitutive equations. The workshop on Modeling of Soft Matter has taken such an integrated approach.
Modeling of metal forming and machining processes : By finite element and soft computing methods
The physics of metal forming and metal removing is normally expressed using non-linear partial differential equations which can be solved using the finite element method (FEM). However, when the process parameters are uncertain and/or the physics of the process is not well understood, soft computing techniques can be used with FEM or alone to model the process.
Modeling of Biological Materials
This interdisciplinary collection of surveys highlights the central role played by the mathematical modeling of mechanical properties having an effect on the biology, chemistry, and physics of living matter. One of the main goals of the book is to present—in a single, self-contained resource—topics that are widely scattered across the literature in a variety of journals having mutually nonintersecting communities of readers, such as applied mathematicians, engineers, biologists, and physicians. Readers coming from diverse backgrounds are provided with basic modeling ideas and tools to address important problems in the medical and health sciences. Presented are appropriate models as well as their implementation through numerical and computer simulations, which may lead to potential technological innovations useful in medicine.
Modeling in Biopharmaceutics, Pharmacokinetics and Pharmacodynamics : Homogeneous and Heterogeneous Approaches
The state of the art in Biopharmaceutics, Pharmacokinetics, and Pharmacodynamics Modeling is presented in this book. It shows how advanced physical and mathematical methods can expand classical models in order to cover heterogeneous drug-biological processes and therapeutic effects in the body. The book is divided into four parts; the first deals with the fundamental principles of fractals, diffusion and nonlinear dynamics; the second with drug dissolution, release, and absorption; the third with empirical, compartmental, and stochastic pharmacokinetic models, and the fourth mainly with nonclassical aspects of pharmacodynamics. The classical models that have relevance and application to these sciences are also considered throughout. Many examples are used to illustrate the intrinsic complexity of drug administration related phenomena in the human, justifying the use of advanced modeling methods.
Modeling Foundations of Economic Property Rights Theory : An Axiomatic Analysis of Economic Agreements
The idea is to construct a kind of mathematical application in which any fundamental formal entity and/or operation has an empirical economic interpretation. This approach is seen as a way to cope with an extreme c- plexity of economic phenomena under consideration and requests for precise formulationofmodelswheremeaningfulanswersandsolutionsofproblemsare only those which are obtained rigorously. The proposed extensions in ma- ematical economics and property rights theory are to provide rich enough foundations to follow complexity of economic property rights in the exact way, and to identify where there is an appropriate method providing a- quate solution, and also to ?nd problems where in general there is no such methodology.
Modeling Excitable Tissue : The EMI Framework
This volume presents a novel computational framework for understanding how collections of excitable cells work. The key approach in the text is to model excitable tissue by representing the individual cells constituting the tissue. This is in stark contrast to the common approach where homogenization is used to develop models where the cells are not explicitly present. The approach allows for very detailed analysis of small collections of excitable cells, but computational challenges limit the applicability in the presence of large collections of cells.
