Mathematical Modeling of Social Relationships, Strawinska-Zanko
Автор: Riley Название: Mathematical Methods for Physics and Engineering ISBN: 0521679710 ISBN-13(EAN): 9780521679718 Издательство: Cambridge Academ Рейтинг: Цена: 7920.00 р. Наличие на складе: Есть (1 шт.) Описание: This highly acclaimed undergraduate textbook teaches all the mathematics for undergraduate courses in the physical sciences. Containing over 800 exercises, half come with hints and answers and, in a separate manual, complete worked solutions. The remaining exercises are intended for unaided homework; full solutions are available to instructors.
Автор: Kot, Mark, Название: Elements of Mathematical Ecology ISBN: 0521001501 ISBN-13(EAN): 9780521001502 Издательство: Cambridge Academ Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An introduction to classical and modern mathematical models, methods, and issues in population ecology. Includes numerous line diagrams, relevant problems and supplementary mathematical and historical material that enhances understanding.
Описание: This concise and elementary introduction to stochastic control and mathematical modelling is designed for researchers in stochastic control theory studying its application in mathematical economics, and for interested economics researchers. Also suitable for graduate students in applied mathematics, mathematical economics, and non-linear PDE theory.
Описание: This richly illustrated third edition provides a thorough training in practical mathematical biology and shows how exciting mathematical challenges can arise from a genuinely interdisciplinary involvement with the biosciences.
Автор: Urszula Strawinska-Zanko; Larry S. Liebovitch Название: Mathematical Modeling of Social Relationships ISBN: 3030095770 ISBN-13(EAN): 9783030095772 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This edited volume presents examples of social science research projects that employ new methods of quantitative analysis and mathematical modeling of social processes. This book presents the fascinating areas of empirical and theoretical investigations that use formal mathematics in a way that is accessible for individuals lacking extensive expertise but still desiring to expand their scope of research methodology and add to their data analysis toolbox. Mathematical Modeling of Social Relationships professes how mathematical modeling can help us understand the fundamental, compelling, and yet sometimes complicated concepts that arise in the social sciences. This volume will appeal to upper-level students and researchers in a broad area of fields within the social sciences, as well as the disciplines of social psychology, complex systems, and applied mathematics.
Автор: Rasmuson Название: Mathematical Modeling in Chemical Engineering ISBN: 1107049695 ISBN-13(EAN): 9781107049697 Издательство: Cambridge Academ Рейтинг: Цена: 9027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A solid introduction, equipping the reader with the insight and skill required to successfully formulate, construct, simplify, evaluate and use mathematical models in chemical engineering. The accompanying problems, tutorials, and projects provide the reader with hands-on experience, and include model formulation at different levels, analysis, parameter estimation and numerical solution.
Автор: Murray, James D. Название: Mathematical Biology I. An Introduction ISBN: 1475777094 ISBN-13(EAN): 9781475777093 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Providing an in-depth look at the practical use of math modeling, it features exercises throughout that are drawn from a variety of bioscientific disciplines - population biology, developmental biology, physiology, epidemiology, and evolution, among others.
Автор: Krishnan S. Hariharan; Piyush Tagade; Sanoop Ramac Название: Mathematical Modeling of Lithium Batteries ISBN: 3319035266 ISBN-13(EAN): 9783319035260 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is unique to be the only one completely dedicated for battery modeling for all components of battery management system (BMS) applications. The contents of this book compliment the multitude of research publications in this domain by providing coherent fundamentals. An explosive market of Li ion batteries has led to aggressive demand for mathematical models for battery management systems (BMS). Researchers from multi-various backgrounds contribute from their respective background, leading to a lateral growth. Risk of this runaway situation is that researchers tend to use an existing method or algorithm without in depth knowledge of the cohesive fundamentals—often misinterpreting the outcome. It is worthy to note that the guiding principles are similar and the lack of clarity impedes a significant advancement. A repeat or even a synopsis of all the applications of battery modeling albeit redundant, would hence be a mammoth task, and cannot be done in a single offering. The authors believe that a pivotal contribution can be made by explaining the fundamentals in a coherent manner. Such an offering would enable researchers from multiple domains appreciate the bedrock principles and forward the frontier.Battery is an electrochemical system, and any level of understanding cannot ellipse this premise. The common thread that needs to run across—from detailed electrochemical models to algorithms used for real time estimation on a microchip—is that it be physics based. Build on this theme, this book has three parts. Each part starts with developing a framework—often invoking basic principles of thermodynamics or transport phenomena—and ends with certain verified real time applications. The first part deals with electrochemical modeling and the second with model order reduction. Objective of a BMS is estimation of state and health, and the third part is dedicated for that. Rules for state observers are derived from a generic Bayesian framework, and health estimation is pursued using machine learning (ML) tools. A distinct component of this book is thorough derivations of the learning rules for the novel ML algorithms. Given the large-scale application of ML in various domains, this segment can be relevant to researchers outside BMS domain as well.The authors hope this offering would satisfy a practicing engineer with a basic perspective, and a budding researcher with essential tools on a comprehensive understanding of BMS models.
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