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Mathematical modelling

See below for a selection of the latest books from Mathematical modelling category. Presented with a red border are the Mathematical modelling books that have been lovingly read and reviewed by the experts at Lovereading. With expert reading recommendations made by people with a passion for books and some unique features Lovereading will help you find great Mathematical modelling books and those from many more genres to read that will keep you inspired and entertained. And it's all free!

Arbres Pour l'Algorithmique

Arbres Pour l'Algorithmique

Author: Brigitte Chauvin, Julien Clement, Daniele Gardy Format: Paperback / softback Release Date: 29/03/2019

Agriculture as a Metaphor for Creativity in All Human Endeavors

Agriculture as a Metaphor for Creativity in All Human Endeavors

Author: Robert S. Anderssen Format: Paperback / softback Release Date: 28/03/2019

This book is a collection of papers presented at the 'Forum Math-for-Industry 2016 ' (FMfl2016), held at Queensland University of Technology, Brisbane, Australia, on November 21-23, 2016. The theme for this unique and important event was Agriculture as a Metaphor for Creativity in All Human Endeavors , and it brought together leading international mathematicians and active researchers from universities and industry to discuss current challenging topics and to promote interactive collaborations between mathematics and industry. The success of agricultural practice relies fundamentally on its interconnections with and dependence on biology and the environment. Both play essential roles, including the biological adaption to cope with environmental challenges of biotic and abiotic stress and global warming. The book highlights the development of mathematics within this framework that successful agricultural practice depends upon and exploits.

Functional Gaussian Approximation for Dependent Structures

Functional Gaussian Approximation for Dependent Structures

Functional Gaussian Approximation for Dependent Structures develops and analyses mathematical models for phenomena that evolve in time and influence each another. It provides a better understanding of the structure and asymptotic behaviour of stochastic processes. Two approaches are taken. Firstly, the authors present tools for dealing with the dependent structures used to obtain normal approximations. Secondly, they apply normal approximations to various examples. The main tools consist of inequalities for dependent sequences of random variables, leading to limit theorems, including the functional central limit theorem and functional moderate deviation principle. The results point out large classes of dependent random variables which satisfy invariance principles, making possible the statistical study of data coming from stochastic processes both with short and long memory. The dependence structures considered throughout the book include the traditional mixing structures, martingale-like structures, and weakly negatively dependent structures, which link the notion of mixing to the notions of association and negative dependence. Several applications are carefully selected to exhibit the importance of the theoretical results. They include random walks in random scenery and determinantal processes. In addition, due to their importance in analysing new data in economics, linear processes with dependent innovations will also be considered and analysed.

Meshing, Geometric Modeling and Numerical Simulation, Volume 2 Metrics, Meshes and Mesh Adaptation

Meshing, Geometric Modeling and Numerical Simulation, Volume 2 Metrics, Meshes and Mesh Adaptation

Author: Paul Louis George, Houman Borouchaki, Frederic Alauzet, Patrick Laug Format: Hardback Release Date: 08/03/2019

Triangulations, and more precisely meshes, are at the heart of many problems relating to a wide variety of scientific disciplines, and in particular numerical simulations of all kinds of physical phenomena. In numerical simulations, the functional spaces of approximation used to search for solutions are defined from meshes, and in this sense these meshes play a fundamental role. This strong link between meshes and functional spaces leads us to consider advanced simulation methods in which the meshes are adapted to the behaviors of the underlying physical phenomena. This book presents the basic elements of this vision of meshing. These mesh adaptations are generally governed by a posteriori error estimators representing an increase of the error with respect to a size or metric. Independently of this metric of calculation, compliance with a geometry can also be calculated using a so-called geometric metric. The notion of mesh thus finds its meaning in the metric of its elements.

Financial Mathematics, Derivatives and Structured Products

Financial Mathematics, Derivatives and Structured Products

Author: Raymond H. Chan, Yves ZY. Guo, Spike T. Lee, Xun Li Format: Hardback Release Date: 07/03/2019

This book introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners. In addition, it equips readers with the necessary knowledge of financial markets needed in order to work as product structurers, traders, sales or risk managers. As the book seeks to unify the derivatives modelling and the financial engineering practice in the market, it will be of interest to financial practitioners and academic researchers alike. Further, it takes a different route from the existing financial mathematics books, and will appeal to students and practitioners with or without a scientific background. The book can also be used as a textbook for the following courses: * Financial Mathematics (undergraduate level) * Stochastic Modelling in Finance (postgraduate level) * Financial Markets and Derivatives (undergraduate level) * Structured Products and Solutions (undergraduate/postgraduate level)

Model Engineering for Simulation

Model Engineering for Simulation

Author: Lin (Computer and Systems Science, Beihang Unversity, China) Zhang Format: Paperback / softback Release Date: 01/03/2019

Model Engineering for Simulation provides a systematic introduction to the implementation of generic, normalized and quantifiable modeling and simulation using DEVS formalism. It describes key technologies relating to model lifecycle management, including model description languages, complexity analysis, model management, service-oriented model composition, quantitative measurement of model credibility, and model validation and verification. The book clearly demonstrates how to construct computationally efficient, object-oriented simulations of DEVS models on parallel and distributed environments.

Mathematical Image Processing

Mathematical Image Processing

Author: Kristian Bredies, Dirk Lorenz Format: Hardback Release Date: 28/02/2019

Mathematical Models of Higher Orders Shells in Temperature Fields

Mathematical Models of Higher Orders Shells in Temperature Fields

Author: Vadim A. Krysko, Jan Awrejcewicz, Maxim V. Zhigalov, Valeriy F. Kirichenko Format: Hardback Release Date: 21/02/2019

This book offers a valuable methodological approach to the state-of-the-art of the classical plate/shell mathematical models, exemplifying the vast range of mathematical models of nonlinear dynamics and statics of continuous mechanical structural members. The main objective highlights the need for further study of the classical problem of shell dynamics consisting of mathematical modeling, derivation of nonlinear PDEs, and of finding their solutions based on the development of new and effective numerical techniques. The book is designed for a broad readership of graduate students in mechanical and civil engineering, applied mathematics, and physics, as well as to researchers and professionals interested in a rigorous and comprehensive study of modeling non-linear phenomena governed by PDEs.

A Primer on Fourier Analysis for the Geosciences

A Primer on Fourier Analysis for the Geosciences

Author: Robin (University of Northampton) Crockett Format: Hardback Release Date: 14/02/2019

Time-series analysis is used to identify and quantify periodic features in datasets and has many applications across the geosciences, from analysing weather data, to solid-Earth geophysical modelling. This intuitive introduction provides a practical 'how-to' guide to basic Fourier theory, with a particular focus on Earth system applications. The book starts with a discussion of statistical correlation, before introducing Fourier series and building to the fast Fourier transform (FFT) and related periodogram techniques. The theory is illustrated with numerous worked examples using R datasets, from Milankovitch orbital-forcing cycles to tidal harmonics and exoplanet orbital periods. These examples highlight the key concepts and encourage readers to investigate more advanced time-series techniques. The book concludes with a consideration of statistical effect size and significance. This useful book is ideal for graduate students and researchers in the Earth system sciences who are looking for an accessible introduction to time-series analysis.

A Primer on Fourier Analysis for the Geosciences

A Primer on Fourier Analysis for the Geosciences

Author: Robin (University of Northampton) Crockett Format: Paperback / softback Release Date: 14/02/2019

Time-series analysis is used to identify and quantify periodic features in datasets and has many applications across the geosciences, from analysing weather data, to solid-Earth geophysical modelling. This intuitive introduction provides a practical 'how-to' guide to basic Fourier theory, with a particular focus on Earth system applications. The book starts with a discussion of statistical correlation, before introducing Fourier series and building to the fast Fourier transform (FFT) and related periodogram techniques. The theory is illustrated with numerous worked examples using R datasets, from Milankovitch orbital-forcing cycles to tidal harmonics and exoplanet orbital periods. These examples highlight the key concepts and encourage readers to investigate more advanced time-series techniques. The book concludes with a consideration of statistical effect size and significance. This useful book is ideal for graduate students and researchers in the Earth system sciences who are looking for an accessible introduction to time-series analysis.

Fault Diagnosis Inverse Problems: Solution with Metaheuristics

Fault Diagnosis Inverse Problems: Solution with Metaheuristics

This book presents a methodology based on inverse problems for use in solutions for fault diagnosis in control systems, combining tools from mathematics, physics, computational and mathematical modeling, optimization and computational intelligence. This methodology, known as fault diagnosis - inverse problem methodology or FD-IPM, unifies the results of several years of work of the authors in the fields of fault detection and isolation (FDI), inverse problems and optimization. The book clearly and systematically presents the main ideas, concepts and results obtained in recent years. By formulating fault diagnosis as an inverse problem, and by solving it using metaheuristics, the authors offer researchers and students a fresh, interdisciplinary perspective for problem solving in these fields. Graduate courses in engineering, applied mathematics and computing also benefit from this work.

Scientific Computing in Electrical Engineering SCEE 2016, St. Wolfgang, Austria, October 2016

Scientific Computing in Electrical Engineering SCEE 2016, St. Wolfgang, Austria, October 2016

Author: Ulrich Langer Format: Paperback / softback Release Date: 08/02/2019

This collection of selected papers presented at the 11th International Conference on Scientific Computing in Electrical Engineering (SCEE), held in St. Wolfgang, Austria, in 2016, showcases the state of the art in SCEE. The aim of the SCEE 2016 conference was to bring together scientists from academia and industry, mathematicians, electrical engineers, computer scientists, and physicists, and to promote intensive discussions on industrially relevant mathematical problems, with an emphasis on the modeling and numerical simulation of electronic circuits and devices, electromagnetic fields, and coupled problems. The focus in methodology was on model order reduction and uncertainty quantification. This extensive reference work is divided into six parts: Computational Electromagnetics, Circuit and Device Modeling and Simulation, Coupled Problems and Multi-Scale Approaches in Space and Time, Mathematical and Computational Methods Including Uncertainty Quantification, Model Order Reduction, and Industrial Applications. Each part starts with a general introduction, followed by the respective contributions. This book will appeal to mathematicians and electrical engineers. Further, it introduces algorithm and program developers to recent advances in the other fields, while industry experts will be introduced to new programming tools and mathematical methods.