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001481269 001__ 1481269
001481269 003__ OCoLC
001481269 005__ 20231031003330.0
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001481269 008__ 230930s2023\\\\si\\\\\\ob\\\\001\0\eng\d
001481269 019__ $$a1400972866
001481269 020__ $$a9789819955435$$q(electronic bk.)
001481269 020__ $$a9819955432$$q(electronic bk.)
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001481269 0247_ $$a10.1007/978-981-99-5543-5$$2doi
001481269 035__ $$aSP(OCoLC)1401056373
001481269 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX
001481269 049__ $$aISEA
001481269 050_4 $$aQA76.9.B45
001481269 08204 $$a005.7$$223/eng/20231013
001481269 1001_ $$aPourroostaei Ardakani, Saeid.
001481269 24510 $$aBig data analytics for smart urban systems /$$cSaeid Pourroostaei Ardakani, Ali Cheshmehzangi.
001481269 260__ $$aSingapore :$$bSpringer,$$c2023.
001481269 300__ $$a1 online resource (143 p.).
001481269 4901_ $$aUrban Sustainability
001481269 500__ $$a5.3 Methodology
001481269 504__ $$aIncludes bibliographical references and index.
001481269 5050_ $$aIntro -- Preface -- Acknowledgements -- About This Book -- Praise for Big Data Analytics for Smart Urban Systems -- Contents -- About the Authors -- 1 Big Data Analytics: An Introduction to Their Applications for Smart Urban Systems -- 1.1 The Emergence of Big Data Analytics -- 1.2 The Aim and Objectives of the Book -- 1.3 The Structure of Two Volumes on Big Data Analytics -- 1.4 A Summary -- Box 1.1 Examples of 'Smart Cities' reports and documents -- Box 1.2 Examples of 'Smart Cities' reports and documents -- Box 1.3 Examples of 'Smart Cities' reports and documents
001481269 5058_ $$aBox 1.4 Examples of 'Smart Cities' reports and documents -- Box 1.5 Examples of 'Smart Cities' reports and documents -- Box 1.6 Examples of 'Smart Cities' reports and documents -- Box 1.7 Examples of 'Smart Cities' reports and documents -- Box 1.8 Examples of 'Smart Cities' reports and documents -- Box 1.9 Examples of 'Smart Cities' reports and documents -- Box 1.10 Examples of 'Smart Cities' reports and documents -- References -- 2 Stock Market Prediction During COVID-19 Pandemic: A Time-Series Big Data Analysis Method -- 2.1 Introduction -- 2.2 Literature Review
001481269 5058_ $$a2.2.1 Big Data Analytics in Stock Markets -- 2.3 Methodology -- 2.3.1 Data Preprocessing -- 2.3.2 Pattern Retrieval Using DTW -- 2.3.3 Feature Selection -- 2.3.4 Predicted Stock Data Generation Using LSTM -- 2.4 Result Analysis and Discussion -- 2.4.1 Data Preprocessing -- 2.4.2 Estimation of Close Price and COVID-19 Data -- 2.4.3 Pattern Selection -- 2.4.4 Feature Selection Result with Analysis -- 2.4.5 Result for LSTM Price Prediction -- 2.4.6 Predicted Price and Covid-19 Data Factors -- 2.5 Conclusion -- References
001481269 5058_ $$a3 A Big Data Solution to Predict Cryptocurrency Market Trends: A Time-Series Machine Learning Approach -- 3.1 Introduction -- 3.2 Literature Review -- 3.2.1 Cryptocurrency Pattern Recognition and Clustering -- 3.2.2 Bitcoin Price Prediction -- 3.3 Methodology -- 3.3.1 Dataset Selection and Pre-processing -- 3.3.2 Data Pattern Recognition via Clustering -- 3.3.3 Predictive Analysis -- 3.4 Result and Discussion -- 3.4.1 Trend Prediction -- 3.5 Conclusion -- References -- 4 Big Data Analytics for Credit Risk Prediction: Machine Learning Techniques and Data Processing Approaches -- 4.1 Introduction
001481269 5058_ $$a4.2 Literature Review -- 4.3 Methodology -- 4.3.1 Dataset and Data Pre-processing -- 4.3.2 Machine Learning Models -- 4.4 Result and Discussion -- 4.5 Conclusion -- References -- 5 Worldwide Mobility Trends and the COVID-19 Pandemic: A Federated Regression Analysis During the pandemic's Early Stage -- 5.1 Introduction -- 5.2 Literature Review on Existing Research Studies -- 5.2.1 Influence Factors -- 5.2.2 Pharmacological and Non-pharmacological Interventions -- 5.2.3 Social Distance Policy -- 5.2.4 Reflection of H1N1 -- 5.2.5 Cultural Susceptibility and Policy -- 5.2.6 Voluntary Mechanisms
001481269 506__ $$aAccess limited to authorized users.
001481269 520__ $$aBig Data Analytics for Smart Urban Systems aims to introduce Big data solutions for urban sustainability smart applications, particularly for smart urban systems. It focuses on intelligent big data which takes the benefits of machine learning to analyse large and rapidly changing datasets in smart urban systems. The state-of-the-art Big data analytics applications are presented and discussed to highlight the feasibility of big data and machine learning solutions to enhance smart urban systems, smart operations, urban management, and urban governance. The key benefits of this book are, (1) to introduce the principles of machine learning-enabled big data analysis in smart urban systems, (2) to present the state-of-the-art data analysis solutions in smart management and operations, and (3) to understand the principles of big data analytics for smart cities and communities. Endorsements Over the many years of collaboration between academia and industry, we noticed the common language is big data; with that, we have developed novel ideas to bridge the gaps and help promote innovation, technologies, and science. - Tian Tang, Independent Researcher, China Big Data Analytics is a fascinating research area, particularly for cities and city transformations. This book is valuable to those who think vigorously and aim to act ahead. - Li Xie, Independent Researcher, China For urban critiques, knowledge trains aspiring opportunities toward outstanding manifestations. Smartness has evolved or/ advanced rambunctious & embracing realities along (with) novel directions and nurturing integrated city knowledge. - Aaron Golden, SELECT Consultants, UK.
001481269 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 13, 2023).
001481269 650_0 $$aBig data$$xSocial aspects.$$0(DLC)sh2012003227
001481269 650_0 $$aBig data$$xEconomic aspects.$$0(DLC)sh2012003227
001481269 650_0 $$aCities and towns$$xData processing.$$zChina$$xGrowth$$0(DLC)sh2009119763
001481269 650_0 $$aSmart cities$$xData processing.$$0(DLC)sh2018000509
001481269 655_0 $$aElectronic books.
001481269 7001_ $$aCheshmehzangi, Ali.
001481269 77608 $$iPrint version:$$aPourroostaei Ardakani, Saeid$$tBig Data Analytics for Smart Urban Systems$$dSingapore : Springer Singapore Pte. Limited,c2023$$z9789819955428
001481269 830_0 $$aUrban sustainability (Springer (Firm))
001481269 852__ $$bebk
001481269 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5543-5$$zOnline Access$$91397441.1
001481269 909CO $$ooai:library.usi.edu:1481269$$pGLOBAL_SET
001481269 980__ $$aBIB
001481269 980__ $$aEBOOK
001481269 982__ $$aEbook
001481269 983__ $$aOnline
001481269 994__ $$a92$$bISE