Hierarchical Optimization and Mathematical Physics, Vladimir Tsurkov
Автор: Vladimir Tsurkov Название: Hierarchical Optimization and Mathematical Physics ISBN: 1461371120 ISBN-13(EAN): 9781461371120 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book should be considered as an introduction to a special dass of hierarchical systems of optimal control, where subsystems are described by partial differential equations of various types.
Автор: Gerald Farin; Bernd Hamann; Hans Hagen Название: Hierarchical and Geometrical Methods in Scientific Visualization ISBN: 364262801X ISBN-13(EAN): 9783642628016 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The nature of the physical Universe has been increasingly better understood in recent years, and cosmological concepts have undergone a rapid evolution (see, e.g., [11], [2],or [5]).
Автор: V. Kulish Название: Hierarchical Methods ISBN: 9401740585 ISBN-13(EAN): 9789401740586 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Experience shows that indeed `systematically remaining` problems are mainly of a complex tech- logical nature (the creation of new generation of especially perfect - croschemes, elements of memory, etc. But let us note that amongst these problems there are always ones solved by our purely intellectual efforts alone.
Автор: Mikul?s Lupt?cik Название: Mathematical Optimization and Economic Analysis ISBN: 146142464X ISBN-13(EAN): 9781461424642 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This monograph is a self-contained introduction to the optimization techniques used in economic modeling such as mathematical programming and data envelopment analysis. This book demonstrates the usefulness of these mathematical tools in quantitative and qualitative economic analysis.
Описание: The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;
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