Methods for Handling Imperfect Spatial Information, Robert Jeansoulin; Odile Papini; Henri Prade; Stev

Автор: Zbigniew W. Ras; William Ribarsky
Название: Advances in Information and Intelligent Systems
ISBN: 364204140X ISBN-13(EAN): 9783642041402
Издательство: Springer
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Цена: 27251.00 р.
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Описание: Recent advances in complex systems, knowledge management, knowledge discovery, and visualization are presented in this review of intelligent systems. The methods and tools described are efficiently applicable to various types of data analysis issues.

Автор: Takahiro Hara; Vladimir I. Zadorozhny; Erik Buchma
Название: Wireless Sensor Network Technologies for the Information Explosion Era
ISBN: 3642263860 ISBN-13(EAN): 9783642263866
Издательство: Springer
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Цена: 19589.00 р.
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Описание: This volume aims to cover both theoretical and practical aspects related to the latest research in the area of wireless sensor networks. It explores directions for future research to enable efficient utilization of WSNs in the information-explosion era.

Автор: Zongmin Ma
Название: Fuzzy Database Modeling of Imprecise and Uncertain Engineering Information
ISBN: 3642067956 ISBN-13(EAN): 9783642067952
Издательство: Springer
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Цена: 23757.00 р.
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Описание: Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema.

Автор: Didier Dubois; Maria Asuncion Lubiano; Henri Prade
Название: Soft Methods for Handling Variability and Imprecision
ISBN: 3540850260 ISBN-13(EAN): 9783540850267
Издательство: Springer
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Цена: 27950.00 р.
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Описание: Gathers contributions to the 4th International Conference on Soft methods in Probability and Statistics. This work aims to present results illustrating such trends that enlarge the statistical and uncertainty modeling traditions, towards the handling of incomplete or subjective information.

Автор: Mathias Uslar; Michael Specht; Sebastian Rohjans;
Название: The Common Information Model CIM
ISBN: 3642442757 ISBN-13(EAN): 9783642442759
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book provides an overview of the development of the Common Information Model (CIM), describes which international projects and roadmaps have already been covered and outlines the basic use cases for CIM. Covers both theoretical and practical aspects.

Автор: Monica Bianchini; Marco Maggini; Franco Scarselli
Название: Innovations in Neural Information Paradigms and Applications
ISBN: 3642040020 ISBN-13(EAN): 9783642040023
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Presenting the fundamentals and practical applications of neural information systems, this volume presents the recent developments in the field. Self-organizing structures, neural grammar networks and model complexity are among the many topics discussed.

Автор: Zbigniew W. Ras; William Ribarsky
Название: Advances in Information and Intelligent Systems
ISBN: 364226087X ISBN-13(EAN): 9783642260872
Издательство: Springer
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Цена: 27251.00 р.
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Описание: Recent advances in complex systems, knowledge management, knowledge discovery, and visualization are presented in this review of intelligent systems. The methods and tools described are efficiently applicable to various types of data analysis issues.

Автор: Zbigniew W. Ras; Alicja Wieczorkowska
Название: Advances in Music Information Retrieval
ISBN: 3642116736 ISBN-13(EAN): 9783642116735
Издательство: Springer
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Цена: 26122.00 р.
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Описание: This book collects research performed in music information retrieval domain, and the outcomes, as well as trends in this research. Four sections cover MIR Methods and Platforms, Harmony, Music Similarity, and Content Based Identification and Retrieval.

Автор: Jorma Rissanen
Название: Information and Complexity in Statistical Modeling
ISBN: 1441922679 ISBN-13(EAN): 9781441922670
Издательство: Springer
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Цена: 15372.00 р.
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Описание: The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The prerequisites include basic probability calculus and statistics.