Modeling Fuzzy Spatiotemporal Data with XML, Ma Zongmin, Bai Luyi, Yan Li

Автор: Ma Zongmin, Bai Luyi, Yan Li
Название: Modeling Fuzzy Spatiotemporal Data with XML
ISBN: 3030419983 ISBN-13(EAN): 9783030419981
Издательство: Springer
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Цена: 139750.00 T
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Описание: The topics covered include representation of fuzzy spatiotemporal XML data, topological relationship determination for fuzzy spatiotemporal XML data, mapping between the fuzzy spatiotemporal relational database model and fuzzy spatiotemporal XML data model, and consistencies in fuzzy spatiotemporal XML data updating.

Автор: Berkay Aydin; Rafal. A Angryk
Название: Spatiotemporal Frequent Pattern Mining from Evolving Region Trajectories
ISBN: 3319998722 ISBN-13(EAN): 9783319998725
Издательство: Springer
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Цена: 51230.00 T
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Описание: This SpringerBrief provides an overview within data mining of spatiotemporal frequent pattern mining from evolving regions to the perspective of relationship modeling among the spatiotemporal objects, frequent pattern mining algorithms, and data access methodologies for mining algorithms. While the focus of this book is to provide readers insight into the mining algorithms from evolving regions, the authors also discuss data management for spatiotemporal trajectories, which has become increasingly important with the increasing volume of trajectories.This brief describes state-of-the-art knowledge discovery techniques to computer science graduate students who are interested in spatiotemporal data mining, as well as researchers/professionals, who deal with advanced spatiotemporal data analysis in their fields. These fields include GIS-experts, meteorologists, epidemiologists, neurologists, and solar physicists.

Автор: Ben Goertzel; Nil Geisweiller; Lucio Coelho; Predr
Название: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
ISBN: 9462390533 ISBN-13(EAN): 9789462390539
Издательство: Springer
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Цена: 93160.00 T
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Описание: The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations.

Автор: John Oyekan
Название: Tracking and Mapping of Spatiotemporal Quantities Using Unicellular Swarm Intelligence
ISBN: 3319274236 ISBN-13(EAN): 9783319274232
Издательство: Springer
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Цена: 121890.00 T
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Описание: The book discusses new algorithms capable ofsearching for, tracking, mapping and providing a visualization of invisiblesubstances. The book also discusses how a computationally tractable multi-agentrobotic controller was developed and used to track as well as provide a visualmap of a spatio-temporal distribution of a substance.

Автор: Li Yan; Zongmin Ma; Fu Zhang
Название: Fuzzy XML Data Management
ISBN: 3642448984 ISBN-13(EAN): 9783642448980
Издательство: Springer
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Цена: 130610.00 T
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Описание: This book details recent advances in fuzzy XML data management. Coverage includes: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models and reasoning of fuzzy XML.

Автор: Li Yan; Zongmin Ma; Fu Zhang
Название: Fuzzy XML Data Management
ISBN: 366250927X ISBN-13(EAN): 9783662509272
Издательство: Springer
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Цена: 104480.00 T
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Описание: This book details recent advances in fuzzy XML data management. Coverage includes: representation of fuzzy XML, query of fuzzy XML, fuzzy database models, extraction of fuzzy XML from fuzzy database models and reasoning of fuzzy XML.

Автор: Li, Lixin
Название: Spatiotemporal Analysis Of Air Pollution And Its Application In Public Health
ISBN: 0128158220 ISBN-13(EAN): 9780128158227
Издательство: Elsevier Science
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Цена: 132500.00 T
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Описание:

Spatiotemporal Analysis of Air Pollution and Its Application in Public Health reviews, in detail, the tools needed to understand the spatial temporal distribution and trends of air pollution in the atmosphere, including how this information can be tied into the diverse amount of public health data available using accurate GIS techniques. By utilizing GIS to monitor, analyze and visualize air pollution problems, it has proven to not only be the most powerful, accurate and flexible way to understand the atmosphere, but also a great way to understand the impact air pollution has in diverse populations.