Автор: Tiumentsev, Yury Название: Neural Network Modeling and Identification of Dynamical Systems ISBN: 0128152540 ISBN-13(EAN): 9780128152546 Издательство: Elsevier Science Рейтинг: Цена: 132500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft.
Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training
Offers application examples of dynamic neural network technologies, primarily related to aircraft
Provides an overview of recent achievements and future needs in this area
Автор: Bernard, Lucas, Nyambuu, Unurjargal (Eds.) Название: Dynamic Modeling, Empirical Macroeconomics, and Finance ISBN: 3319398857 ISBN-13(EAN): 9783319398853 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edited volume, with contributions by area experts, offers discussions on a range of evolving topics in economics and social development. At center are important issues central to sustainable development, economic growth, technological change, the economics of climate change, commodity markets, long wave theory, non-linear dynamic models, and boom-bust cycles. This is an excellent reference for academic and professional economists interested in emerging areas of empirical macroeconomics and finance. For policy makers and curious readers alike, it is also an outstanding introduction to the economic thinking of those who seek a holistic and all-compassing approach in economic theory and policy. Looking into new data and methodology, this book offers fresh approaches in a post-crisis environment. Set in a profound understanding of the diverse currents within the many traditions of economic thought, this book pushes the established frontiers of economic thinking. It is dedicated to a leading scholar in the areas covered in this book, Willi Semmler.
Автор: Marius Ooms Название: Empirical Vector Autoregressive Modeling ISBN: 3540577076 ISBN-13(EAN): 9783540577072 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This monograph applies multivariate linear time series models to periodical economic data in order to describe important dynamic relationships between the variables. The text stresses practical applications and the selection of the correct analytical tools.
Автор: Francis X. Diebold Название: Empirical Modeling of Exchange Rate Dynamics ISBN: 3540189661 ISBN-13(EAN): 9783540189664 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this monograph, we use optimal model specification techniques, including formal unit root tests which allow for trend, and find that all of the exchange rates studied do in fact evolve as random walks or random walks with drift (to a very close approximation).
Автор: Pardo Scott Название: Empirical Modeling and Data Analysis for Engineers and Appli ISBN: 3319327674 ISBN-13(EAN): 9783319327679 Издательство: Springer Рейтинг: Цена: 62410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions.
While science is about discovery, the primary paradigm of engineering and 'applied science' is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems.
That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as 'Statistics for Engineers and Scientists' without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes.
Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models.Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation)Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process.Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter.
The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.
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