BOOKS - Spatiotemporal Data Analytics and Modeling Techniques and Applications
Spatiotemporal Data Analytics and Modeling Techniques and Applications - John A, Satheesh Abimannan, El-Sayed M. El-Alfy 2024 PDF | EPUB Springer BOOKS
ECO~14 kg CO²

1 TON

Views
32058

Telegram
 
Spatiotemporal Data Analytics and Modeling Techniques and Applications
Author: John A, Satheesh Abimannan, El-Sayed M. El-Alfy
Year: 2024
Pages: 253
Format: PDF | EPUB
File size: 18.9 MB
Language: ENG



Pay with Telegram STARS
Spatiotemporal Data Analytics and Modeling Techniques and Applications The rapid development of data analytics and modeling techniques has revolutionized our understanding of spatiotemporal phenomena, enabling us to analyze and predict complex events and processes in various fields such as geography, transportation, healthcare, and finance. This book provides a comprehensive overview of the current state of spatiotemporal data analytics and modeling techniques and their applications in different domains. It covers topics such as spatial data mining, spatial regression, space-time clustering, and space-time forecasting, providing readers with a solid foundation in these areas. The book also explores the challenges and limitations of spatiotemporal data analysis and discusses future research directions in this field. The need to study and understand the process of technology evolution As technology continues to evolve at an unprecedented pace, it is essential to understand the process of technological advancement and its impact on human society. The development of spatiotemporal data analytics and modeling techniques is one such advancement that has transformed our ability to analyze and understand complex events and processes.
Методы и приложения для анализа и моделирования пространственно-временных данных Быстрое развитие методов анализа и моделирования данных произвело революцию в нашем понимании пространственно-временных явлений, что позволило нам анализировать и прогнозировать сложные события и процессы в различных областях, таких как география, транспорт, здравоохранение и финансы. В этой книге представлен всесторонний обзор текущего состояния методов анализа и моделирования пространственно-временных данных и их применения в различных областях. Он охватывает такие темы, как анализ пространственных данных, пространственная регрессия, пространственно-временная кластеризация и пространственно-временное прогнозирование, предоставляя читателям прочную основу в этих областях. В книге также рассматриваются проблемы и ограничения пространственно-временного анализа данных и обсуждаются будущие направления исследований в этой области. Необходимость изучения и понимания процесса эволюции технологий Поскольку технологии продолжают развиваться беспрецедентными темпами, важно понимать процесс технологического прогресса и его влияние на человеческое общество. Развитие методов анализа и моделирования пространственно-временных данных является одним из таких достижений, которое изменило нашу способность анализировать и понимать сложные события и процессы.
Méthodes et applications pour l'analyse et la modélisation des données spatio-temporelles développement rapide des méthodes d'analyse et de modélisation des données a révolutionné notre compréhension des phénomènes spatio-temporels, nous permettant d'analyser et de prédire des événements et processus complexes dans différents domaines tels que la géographie, les transports, la santé et la finance. Ce livre donne un aperçu complet de l'état actuel des méthodes d'analyse et de modélisation des données spatio-temporelles et de leur application dans différents domaines. Il couvre des sujets tels que l'analyse des données spatiales, la régression spatiale, le regroupement spatio-temporel et la prévision spatio-temporelle, offrant aux lecteurs une base solide dans ces domaines. livre examine également les défis et les limites de l'analyse spatio-temporelle des données et examine les orientations futures de la recherche dans ce domaine. La nécessité d'étudier et de comprendre le processus d'évolution de la technologie Alors que la technologie continue d'évoluer à un rythme sans précédent, il est important de comprendre le processus de progrès technologique et son impact sur la société humaine. développement des techniques d'analyse et de modélisation des données spatio-temporelles est l'une de ces avancées qui ont modifié notre capacité à analyser et à comprendre des événements et processus complexes.
Métodos y aplicaciones para el análisis y modelado de datos espacio-temporales rápido desarrollo de los métodos de análisis y modelado de datos ha revolucionado nuestra comprensión de los fenómenos espacio-temporales, lo que nos ha permitido analizar y predecir eventos y procesos complejos en diferentes áreas como geografía, transporte, salud y finanzas. Este libro ofrece una visión general completa del estado actual de los métodos de análisis y modelado de datos espacio-temporales y sus aplicaciones en diferentes campos. Abarca temas como el análisis de datos espaciales, la regresión espacial, la agrupación espacio-temporal y la predicción espacio-tiempo, proporcionando a los lectores una base sólida en estas áreas. libro también aborda los desafíos y limitaciones del análisis espacio-temporal de datos y discute las futuras líneas de investigación en este campo. La necesidad de estudiar y comprender el proceso de evolución de la tecnología A medida que la tecnología continúa evolucionando a un ritmo sin precedentes, es importante comprender el proceso de progreso tecnológico y su impacto en la sociedad humana. desarrollo de métodos de análisis y modelado de datos espacio-temporales es uno de esos avances que han alterado nuestra capacidad de analizar y entender eventos y procesos complejos.
Metodi e applicazioni per l'analisi e la simulazione dei dati spazio-temporali Lo sviluppo rapido delle tecniche di analisi e modellazione dei dati ha rivoluzionato la nostra comprensione dei fenomeni spazio-temporali, consentendoci di analizzare e prevedere eventi e processi complessi in diversi settori quali geografia, trasporti, sanità e finanza. Questo libro fornisce una panoramica completa dello stato attuale delle tecniche di analisi e simulazione dei dati spazio-temporali e delle relative applicazioni in diversi ambiti. Include argomenti quali l'analisi dei dati spaziali, la regressione spaziale, il clustering spazio-temporale e la previsione spazio-tempo, fornendo ai lettori una base solida in queste aree. Il libro affronta anche i problemi e le limitazioni dell'analisi spazio-tempo dei dati e discute i futuri percorsi di ricerca in questo campo. La necessità di studiare e comprendere l'evoluzione della tecnologia Poiché la tecnologia continua a crescere a un ritmo senza precedenti, è importante comprendere il processo di progresso tecnologico e il suo impatto sulla società umana. Lo sviluppo delle tecniche di analisi e simulazione dei dati spazio-tempo è uno di questi progressi che ha cambiato la nostra capacità di analizzare e comprendere eventi e processi complessi.
Methoden und Anwendungen zur Analyse und Modellierung von Raum-Zeit-Daten Die rasante Entwicklung von Methoden zur Analyse und Modellierung von Daten hat unser Verständnis von Raum-Zeit-Phänomenen revolutioniert und es uns ermöglicht, komplexe Ereignisse und Prozesse in verschiedenen Bereichen wie Geographie, Verkehr, Gesundheit und Finanzen zu analysieren und vorherzusagen. Dieses Buch bietet einen umfassenden Überblick über den aktuellen Stand der Methoden zur Analyse und Modellierung von Raum-Zeit-Daten und deren Anwendung in verschiedenen Bereichen. Es umfasst Themen wie räumliche Datenanalyse, räumliche Regression, Raum-Zeit-Clustering und Raum-Zeit-Vorhersage und bietet den sern eine solide Grundlage in diesen Bereichen. Das Buch befasst sich auch mit den Herausforderungen und Grenzen der räumlich-zeitlichen Datenanalyse und diskutiert zukünftige Forschungsrichtungen in diesem Bereich. Die Notwendigkeit, den Prozess der Technologieentwicklung zu studieren und zu verstehen Da sich die Technologie in einem beispiellosen Tempo weiterentwickelt, ist es wichtig, den Prozess des technologischen Fortschritts und seine Auswirkungen auf die menschliche Gesellschaft zu verstehen. Die Entwicklung von Methoden zur Analyse und Modellierung von Raum-Zeit-Daten ist eine solche Errungenschaft, die unsere Fähigkeit verändert hat, komplexe Ereignisse und Prozesse zu analysieren und zu verstehen.
''
Mekansal-Zamansal Veri Analizi ve Modellemesi için Yöntemler ve Uygulamalar Veri analizi ve modelleme yöntemlerinin hızlı gelişimi, mekansal-zamansal fenomenleri anlamada devrim yarattı ve coğrafya, ulaşım, sağlık ve finans gibi çeşitli alanlarda karmaşık olayları ve süreçleri analiz etmemize ve tahmin etmemize olanak sağladı. Bu kitap, mekansal-zamansal verileri analiz etme ve modelleme yöntemlerinin mevcut durumuna ve çeşitli alanlardaki uygulamalarına kapsamlı bir genel bakış sunmaktadır. Uzamsal veri analizi, uzamsal regresyon, uzamsal kümeleme ve uzamsal tahmin gibi konuları kapsar ve okuyuculara bu alanlarda sağlam bir temel sağlar. Kitap ayrıca spatiotemporal veri analizinin zorluklarını ve sınırlamalarını ele almakta ve bu alandaki gelecekteki araştırma yönlerini tartışmaktadır. Teknolojinin evrim sürecini inceleme ve anlama ihtiyacı Teknoloji benzeri görülmemiş bir hızda gelişmeye devam ederken, teknolojik ilerleme sürecini ve insan toplumu üzerindeki etkisini anlamak önemlidir. Mekansal-zamansal verileri analiz etmek ve modellemek için yöntemlerin geliştirilmesi, karmaşık olayları ve süreçleri analiz etme ve anlama yeteneğimizi dönüştüren böyle bir ilerlemedir.
時空數據分析和建模的方法和應用數據分析和建模技術的迅速發展徹底改變了我們對時空現象的理解,使我們能夠分析和預測地理、交通、衛生和金融等不同領域的復雜事件和過程。本書全面概述了時空數據分析和建模方法的現狀及其在各個領域的應用。它涵蓋了諸如空間數據分析,空間回歸,時空聚類和時空預測之類的主題,為讀者提供了這些領域的堅實基礎。該書還探討了時空數據分析的問題和局限性,並討論了該領域的未來研究方向。隨著技術繼續以前所未有的速度發展,必須了解技術進步及其對人類社會的影響。時空數據分析和建模方法的發展是這樣的進步之一,改變了我們分析和理解復雜事件和過程的能力。

You may also be interested in:

Real-Time Big Data Analytics: Emerging Architecture
Data-Driven Modelling and Predictive Analytics in Business and Finance
Real-Time Big Data Analytics Emerging Architecture
Data Analytics A Theoretical and Practical View from the EDISON Project
AIoT and Big Data Analytics for Smart Healthcare Applications
Data Curious: Applying Agile Analytics for Better Business Decisions
Pivoting Government through Digital Transformation (Data Analytics Applications)
IoT, Machine Learning and Data Analytics for Smart Healthcare
Data Analytics A Theoretical and Practical View from the EDISON Project
Blockchain Transaction Data Analytics Complex Network Approaches
Data Science for Decision Makers Using Analytics and Case Studies
Financial Data Analytics with Machine Learning, Optimization and Statistics
IoT, Machine Learning and Data Analytics for Smart Healthcare
Big Data Analytics for Connected Vehicles and Smart Cities
Data-Driven Modelling and Predictive Analytics in Business and Finance
Data Analytics Approaches in Educational Games and Gamification Systems
AIoT and Big Data Analytics for Smart Healthcare Applications
Demystifying Big Data Analytics for Industries and Smart Societies
Predictive Analytics and Data Mining Concepts and Practice with RapidMiner
Data Analytics and Machine Learning for Integrated Corridor Management
Statistical Process Control and Data Analytics, Eighth Edition
Big Data Analytics Tools and Technology for Effective Planning
Advanced Analytics with Spark Patterns for Learning from Data at Scale
Data Analytics and Machine Learning for Integrated Corridor Management
Machine Learning Approach for Cloud Data Analytics in IoT
Learning Spark Lightning-Fast Data Analytics, Second Edition
Advanced Deep Learning Applications in Big Data Analytics
Internet of Things and Big Data Analytics-Based Manufacturing
Financial Data Analytics with Machine Learning, Optimization and Statistics
Data Analytics Systems Engineering - Cybersecurity - Project Management
Big Data Analytics with Applications in Insider Threat Detection
AIoT and Big Data Analytics for Smart Healthcare Applications
Microsoft Excel 2010 Data Analysis and Business Modeling
Microsoft Excel 2013 Data Analysis and Business Modeling
Ship Modeling Simplified Tips and Techniques for Model Construction from Kits
Knowledge Modelling and Big Data Analytics in Healthcare: Advances and Applications
Data Analytics for IT Networks Developing Innovative Use Cases (Final version)
Data Analytics for Smart Infrastructure Asset Management and Network Performance
Meta-Analytics Consensus Approaches and System Patterns for Data Analysis
Creating Value with Big Data Analytics Making Smarter Marketing Decisions