Spatiotemporal Data Analytics And Modeling
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Spatiotemporal Data Analytics And Modeling
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Author : John A
language : en
Publisher: Springer Nature
Release Date : 2024-04-15
Spatiotemporal Data Analytics And Modeling written by John A and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.
With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services. A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting,and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things.
Spatio Temporal Graph Data Analytics
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Author : Venkata M. V. Gunturi
language : en
Publisher: Springer
Release Date : 2017-12-15
Spatio Temporal Graph Data Analytics written by Venkata M. V. Gunturi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-15 with Computers categories.
This book highlights some of the unique aspects of spatio-temporal graph data from the perspectives of modeling and developing scalable algorithms. The authors discuss in the first part of this book, the semantic aspects of spatio-temporal graph data in two application domains, viz., urban transportation and social networks. Then the authors present representational models and data structures, which can effectively capture these semantics, while ensuring support for computationally scalable algorithms. In the first part of the book, the authors describe algorithmic development issues in spatio-temporal graph data. These algorithms internally use the semantically rich data structures developed in the earlier part of this book. Finally, the authors introduce some upcoming spatio-temporal graph datasets, such as engine measurement data, and discuss some open research problems in the area. This book will be useful as a secondary text for advanced-level students entering into relevant fields of computer science, such as transportation and urban planning. It may also be useful for researchers and practitioners in the field of navigational algorithms.
Spatiotemporal Data Analysis
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Author : Gidon Eshel
language : en
Publisher: Princeton University Press
Release Date : 2012
Spatiotemporal Data Analysis written by Gidon Eshel and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Mathematics categories.
How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China.
Bayesian Modeling Of Spatio Temporal Data With R
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Author : Sujit Sahu
language : en
Publisher: CRC Press
Release Date : 2022-03-01
Bayesian Modeling Of Spatio Temporal Data With R written by Sujit Sahu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Mathematics categories.
Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. Key features of the book: • Accessible detailed discussion of a majority of all aspects of Bayesian methods and computations with worked examples, numerical illustrations and exercises • A spatial statistics jargon buster chapter that enables the reader to build up a vocabulary without getting clouded in modeling and technicalities • Computation and modeling illustrations are provided with the help of the dedicated R package bmstdr, allowing the reader to use well-known packages and platforms, such as rstan, INLA, spBayes, spTimer, spTDyn, CARBayes, CARBayesST, etc • Included are R code notes detailing the algorithms used to produce all the tables and figures, with data and code available via an online supplement • Two dedicated chapters discuss practical examples of spatio-temporal modeling of point referenced and areal unit data • Throughout, the emphasis has been on validating models by splitting data into test and training sets following on the philosophy of machine learning and data science This book is designed to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers, from mathematicians and statisticians to practitioners in the applied sciences. It presents most of the modeling with the help of R commands written in a purposefully developed R package to facilitate spatio-temporal modeling. It does not compromise on rigour, as it presents the underlying theories of Bayesian inference and computation in standalone chapters, which would be appeal those interested in the theoretical details. By avoiding hard core mathematics and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists.
Applied Spatial Data Analysis With R
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Author : Roger S. Bivand
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-08-24
Applied Spatial Data Analysis With R written by Roger S. Bivand and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-24 with Medical categories.
We began writing this book in parallel with developing software for handling and analysing spatial data withR (R Development Core Team, 2008). - though the book is now complete, software development will continue, in the R community fashion, of rich and satisfying interaction with users around the world, of rapid releases to resolve problems, and of the usual joys and frust- tions of getting things done. There is little doubt that without pressure from users, the development ofR would not have reached its present scale, and the same applies to analysing spatial data analysis withR. It would, however, not be su?cient to describe the development of the R project mainly in terms of narrowly de?ned utility. In addition to being a communityprojectconcernedwiththedevelopmentofworld-classdataana- sis software implementations, it promotes speci?c choices with regard to how data analysis is carried out.R is open source not only because open source software development, including the dynamics of broad and inclusive user and developer communities, is arguably an attractive and successful development model.
Hierarchical Modeling And Analysis For Spatial Data
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Author : Sudipto Banerjee
language : en
Publisher: CRC Press
Release Date : 2003-12-17
Hierarchical Modeling And Analysis For Spatial Data written by Sudipto Banerjee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-12-17 with Mathematics categories.
Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,
Fundamentals Of Spatial Analysis And Modelling
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Author : Jay Gao
language : en
Publisher: CRC Press
Release Date : 2021-12-21
Fundamentals Of Spatial Analysis And Modelling written by Jay Gao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-21 with Technology & Engineering categories.
This textbook provides comprehensive and in-depth explanations of all topics related to spatial analysis and spatiotemporal simulation, including how spatial data are acquired, represented digitally, and spatially aggregated. Also features the nature of space and how it is measured. Descriptive, explanatory, and inferential analyses are covered for point, line, and area data. It captures the latest developments in spatiotemporal simulation with cellular automata and agent-based modelling, and through practical examples discusses how spatial analysis and modelling can be implemented in different computing platforms. A much-needed textbook for a course at upper undergraduate and postgraduate levels.
Data Analytics In Professional Soccer
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Author : Daniel Link
language : en
Publisher: Springer
Release Date : 2018-02-16
Data Analytics In Professional Soccer written by Daniel Link and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-16 with Computers categories.
Daniel Link explores how data analytics can be used for studying performance in soccer. Based on spatiotemporal data from the German Bundesliga, the six individual studies in this book present innovative mathematical approaches for game analysis and player assessment. The findings can support coaches and analysts to improve performance of their athletes and inspire other researchers to advance the research field of sports analytics.
Using R For Bayesian Spatial And Spatio Temporal Health Modeling
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Author : Andrew Lawson
language : en
Publisher: Chapman & Hall/CRC The R Series
Release Date : 2023-05
Using R For Bayesian Spatial And Spatio Temporal Health Modeling written by Andrew Lawson and has been published by Chapman & Hall/CRC The R Series this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05 with Bayesian statistical decision theory categories.
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies.
Geospatial Analysis And Modelling Of Urban Structure And Dynamics
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Author : Bin Jiang
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-06-16
Geospatial Analysis And Modelling Of Urban Structure And Dynamics written by Bin Jiang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-16 with Science categories.
A Coming of Age: Geospatial Analysis and Modelling in the Early Twenty First Century Forty years ago when spatial analysis first emerged as a distinct theme within geography’s quantitative revolution, the focus was largely on consistent methods for measuring spatial correlation. The concept of spatial au- correlation took pride of place, mirroring concerns in time-series analysis about similar kinds of dependence known to distort the standard probability theory used to derive appropriate statistics. Early applications of spatial correlation tended to reflect geographical patterns expressed as points. The perspective taken on such analytical thinking was founded on induction, the search for pattern in data with a view to suggesting appropriate hypotheses which could subsequently be tested. In parallel but using very different techniques came the development of a more deductive style of analysis based on modelling and thence simulation. Here the focus was on translating prior theory into forms for generating testable predictions whose outcomes could be compared with observations about some system or phenomenon of interest. In the intervening years, spatial analysis has broadened to embrace both inductive and deductive approaches, often combining both in different mixes for the variety of problems to which it is now applied.