Spatiotemporal Analytics, Bakhshandeh, Behnam Rothwell, William J. Imroz, So
Автор: Ma Zongmin, Bai Luyi, Yan Li Название: Modeling Fuzzy Spatiotemporal Data with XML ISBN: 3030419983 ISBN-13(EAN): 9783030419981 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Ma Zongmin, Bai Luyi, Yan Li Название: Modeling Fuzzy Spatiotemporal Data with XML ISBN: 3030420019 ISBN-13(EAN): 9783030420017 Издательство: Springer Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Xiaobin Jin; Yinkang Zhou; Xuhong Yang; Yinong Che Название: Historical Farmland in China During 1661-1980 ISBN: 3319891146 ISBN-13(EAN): 9783319891149 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Поставка под заказ.
Описание:
This book explores various approaches to reconstruct the spatial and temporal distribution of historical farmland in China. The book contains background information about political regimes, economic and social development, population changes and land resource utilization in the past 300 years in China. A literature review focuses on the assumptions, methodologies and models of reconstructing historical land-use datasets while addresses accuracy evaluation issues. Historical population size, its growth rate, and the evolution of spatial-temporal patterns of farmland in China have also been discussed. Almost all available historical data about farmland such as historical documents, archives, taxation records, statistics and research outcomes have been collected to reconstruct the amount of historical farmland. With a few principles and assumptions, a delicate Cellular Automaton (CA) and Multi-Agents (MAS) model based on bottom-up management scheme has been applied to derive the spatial-temporal distribution of farmland with the 1km*1km grid resolution for the period between 1661 and 1980 in China. Suggestions for future studies related to reconstructing historical land-use changes are then provided.
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.
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