Mathematical modelling

Researchers working with nonlinear programming often claim "e;the word is non- linear"e; indicating that real applications require nonlinear modeling.

PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial production processes and other "e;noisy"e; systems where the main emphasis is process optimization.

This monograph presents a rigorous mathematical framework for a linear elastic model arising from volcanology that explains deformation effects generated by inflating or deflating magma chambers in the Earth's interior.

Enrique Castillo is a leading figure in several mathematical and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications.

Mathematical ecology is the application of mathematics to describe and understand ecosystems.

Designing small structures necessitates an a priori understanding of various device behaviors.

This book provides a tutorial in the use of Altair Compose and Altair Activate, software packages that provide system modeling and simulation facilities.

A new and unique way of understanding the translation of concepts and natural language into mathematical expressions Transforming a body of text into corresponding mathematical expressions and models is traditionally viewed and taught as a mathematical problem; it is also a task that most find difficult.

25 Problems for STEM Education introduces a new and emerging course for undergraduate STEM programs called Physical-Mathematical Informatics.

This new book focuses on nanomaterial development as well as investigations of combustion and explosion processes.

The topic of dynamic models tends to be splintered across various disciplines, making it difficult to uniformly study the subject.

A comprehensive summary of species distribution modeling methods integrating ecological and statistical models with spatial data, and a framework for implementation.

This work is devoted to the late Ukrainian computer scientist V.

Modelling with Ordinary Differential Equations: A Comprehensive Approach aims to provide a broad and self-contained introduction to the mathematical tools necessary to investigate and apply ODE models.

This book presents the proceedings of the 5th International Conference on Reliability Safety & Hazard-2024, held in Mumbai during February 21-24, 2024.

The long-awaited, comprehensive guide to practical credit risk modeling Credit Risk Analytics provides a targeted training guide for risk managers looking to efficiently build or validate in-house models for credit risk management.

The book presents recent applications and developments in the field of control of industrial systems, covering a wide range of modeling and feedback control using various robust approaches such as fuzzy systems, sliding mode control, and H-infinity.

SuperFractals, first published in 2006, describes mathematics and algorithms for the first time in book form, with breathtaking colour pictures.

Using a practical, hands-on approach, this book will teach anyone how to carry out Bayesian analyses and interpret the results.

Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training.

Uses a wide variety of applications to demonstrate the universality of mathematical techniques in describing and analysing natural phenomena.

Groundwater is a vital source of water throughout the world.

This book, following the three published volumes of the book, provides the main purpose to collect research papers and review papers to provide an overview of the main issues, results, and open questions in the cutting-edge research on the fields of modeling, optimization, and dynamics and their applications to biology, economy, energy, industry, physics, psychology and finance.

Industries rely more and more on advanced technology.

This novel, interdisciplinary text achieves an integration of empirical data and theory with the aid of mathematical models and statistical methods.

This book mainly provides recent advances in finite-time and fixed-time control issues for complex networks and neural networks.

Mathematical Modeling for Business Analytics is written for decision makers at all levels.

This monograph establishes a theory of classification and translation closedness of time scales, a topic that was first studied by S.

The first book of its kind to cover a wide range of computational methods for electromagnetic phenomena.

Financial analysis, modellng, simulation and knowledge engineering have become essential to the survival of every enterprise.

A guide to solving numerical problems in the biological sciences, with extensive worked examples and exercises of varying difficulty.

This entertaining introduction to advanced numerical modeling aims to lead the reader on a journey towards theholy grail of numerical simulation, i.

A user-oriented, practical introduction outlining methods for analysing actuarial and financial risk.

Written in a rigorous yet logical and easy to use style, spanning a range of disciplines, including business, mathematics, finance and economics, this comprehensive textbook offers a systematic, self-sufficient yet concise presentation of the main topics and related parts of stochastic analysis and statistical finance that are covered in the majori

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.

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.

In complementarity theory, which is a relatively new domain of applied mathematics, several kinds of mathematical models and problems related to the study of equilibrium are considered from the point of view of physics as well as economics.

COMPREHENSIVE COVERAGE OF SHADERS, THE PROGRAMMABLE PIPELINE AND WEBGLFrom geometric primitives to animation to 3D modeling to lighting, shading and texturing, Computer Graphics Through OpenGL(R): From Theory to Experiments is a comprehensive introduction to computer graphics which uses an active learning style to teach key concepts.

This book covers a wide range of topics on the role of Artificial Intelligence, Machine Learning, and Big Data for healthcare applications and deals with the ethical issues and concerns associated with it.

This volume presents a selection of advanced case studies that address a substantial range of issues and challenges arising in space engineering.

This book constitutes an up-to-date account of principles, methods, and tools for mathematical and statistical modelling in a wide range of research fields, including medicine, health sciences, biology, environmental science, engineering, physics, chemistry, computation, finance, economics, and social sciences.

Features an authentic and engaging approach to mathematical modeling driven by real-world applications With a focus on mathematical models based on real and current data, Models for Life: An Introduction to Discrete Mathematical Modeling with Microsoft Office Excel guides readers in the solution of relevant, practical problems by introducing both mathematical and Excel techniques.

This volume contains a selection of contributions that were presented at the Modeling and Optimization: Theory and Applications Conference (MOPTA) held at Lehigh University in Bethlehem, Pennsylvania, USA on July 30-August 1, 2012.

A new approach to the fast-developing world of neural hydrological modelling, this book is essential reading for academics and researchers in the fields of water sciences, civil engineering, hydrology and physical geography.

The analysis and design of engineering and industrial systems has come to rely heavily on the use of optimization techniques.

A significantly revised and improved introduction to a critical aspect of scientific computation Matrix computations lie at the heart of most scientific computational tasks.

In the 1960s and 1970s, mathematical biologists Sir Robert M.

Covering a broad range of topics, this text provides a comprehensive survey of the modelling of chaotic dynamics and complexity in the natural and social sciences.

Introduction to Mathematical Modeling and Computer Simulations is written as a textbook for readers who want to understand the main principles of Modeling and Simulations in settings that are important for the applications, without using the profound mathematical tools required by most advanced texts.

This book reviews the latest risk-based techniques to protect national interests from invasive pests and pathogens before, at and within national borders.