Mathematical modeling in economics, ecology and the environment, Hritonenko, Natali Yatsenko, Yuri
Старое издание
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.
Автор: A.L. Koch; Joseph A. Robinson; George A. Milliken Название: Mathematical Modeling in Microbial Ecology ISBN: 146136826X ISBN-13(EAN): 9781461368267 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From the Chapman & Hall Microbiology Series this unique resource offers specific experimental and practical applications of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to test whether the models provide a good representation of the system.
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: 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.
Автор: Natali Hritonenko; Yuri Yatsenko Название: Mathematical Modeling in Economics, Ecology and the Environment ISBN: 1489977201 ISBN-13(EAN): 9781489977205 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With comprehensive treatment of applied mathematical modeling in economics, population biology, and environmental science, this popular publication has been updated to textbook format for its second edition, which emphasizes control and optimization.
Автор: A.L. Koch; Joseph A. Robinson; George A. Milliken Название: Mathematical Modeling in Microbial Ecology ISBN: 0412035111 ISBN-13(EAN): 9780412035111 Издательство: Springer Рейтинг: Цена: 30606.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: From the Chapman & Hall Microbiology Series this unique resource offers specific experimental and practical applications of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to test whether the models provide a good representation of the system.
Описание: Presents a broad range of topics in the field of mathematical modeling in the biological sciences. This work examines the central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.
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