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Big Data Analytics For Sustainable Computing

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Big Data Analytics For Sustainable Computing

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Author : Haldorai, Anandakumar
language : en
Publisher: IGI Global
Release Date : 2019-09-20

Big Data Analytics For Sustainable Computing written by Haldorai, Anandakumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Computers categories.

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

Big Data Analysis For Green Computing

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Author : Rohit Sharma
language : en
Publisher: CRC Press
Release Date : 2021-10-28

Big Data Analysis For Green Computing written by Rohit Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-28 with Computers categories.

This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics. Big Data Analysis for Green Computing: Concepts and Applications presents the latest technologies and covers the major challenges, issues, and advances of big data and data analytics in green computing. It explores basic as well as high-level concepts. It also includes the use of machine learning using big data and discusses advanced system implementation for smart cities. The book is intended for business and management educators, management researchers, doctoral scholars, university professors, policymakers, and higher academic research organizations.

Machine Intelligence And Data Analytics For Sustainable Future Smart Cities

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Author : Uttam Ghosh
language : en
Publisher: Springer Nature
Release Date : 2021-05-31

Machine Intelligence And Data Analytics For Sustainable Future Smart Cities written by Uttam Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-31 with Technology & Engineering categories.

This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.

Big Data Analysis For Green Computing

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Author : Rohit Sharma
language : en
Publisher: CRC Press
Release Date : 2021-10-28

Smart Sustainable Cities Of The Future

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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-01-11

Smart Sustainable Cities Of The Future written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Political Science categories.

This book is intended to help explore the field of smart sustainable cities in its complexity, heterogeneity, and breadth, the many faces of a topical subject of major importance for the future that encompasses so much of modern urban life in an increasingly computerized and urbanized world. Indeed, sustainable urban development is currently at the center of debate in light of several ICT visions becoming achievable and deployable computing paradigms, and shaping the way cities will evolve in the future and thus tackle complex challenges. This book integrates computer science, data science, complexity science, sustainability science, system thinking, and urban planning and design. As such, it contains innovative computer–based and data–analytic research on smart sustainable cities as complex and dynamic systems. It provides applied theoretical contributions fostering a better understanding of such systems and the synergistic relationships between the underlying physical and informational landscapes. It offers contributions pertaining to the ongoing development of computer–based and data science technologies for the processing, analysis, management, modeling, and simulation of big and context data and the associated applicability to urban systems that will advance different aspects of sustainability. This book seeks to explicitly bring together the smart city and sustainable city endeavors, and to focus on big data analytics and context-aware computing specifically. In doing so, it amalgamates the design concepts and planning principles of sustainable urban forms with the novel applications of ICT of ubiquitous computing to primarily advance sustainability. Its strength lies in combining big data and context–aware technologies and their novel applications for the sheer purpose of harnessing and leveraging the disruptive and synergetic effects of ICT on forms of city planning that are required for future forms of sustainable development. This is because the effects of such technologies reinforce one another as to their efforts for transforming urban life in a sustainable way by integrating data–centric and context–aware solutions for enhancing urban systems and facilitating coordination among urban domains. This timely and comprehensive book is aimed at a wide audience across science, academia industry, and policymaking. It provides the necessary material to inform relevant research communities of the state–of–the–art research and the latest development in the area of smart sustainable urban development, as well as a valuable reference for planners, designers, strategists, and ICT experts who are working towards the development and implementation of smart sustainable cities based on big data analytics and context–aware computing.

Big Data Analytics For Sustainable Computing

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Author :
language : de
Publisher:
Release Date : 2020

Big Data Analytics For Sustainable Computing written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

The Green Computing Book

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Author : Wu-chun Feng
language : en
Publisher: CRC Press
Release Date : 2014-06-16

The Green Computing Book written by Wu-chun Feng and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-16 with Computers categories.

State-of-the-Art Approaches to Advance the Large-Scale Green Computing Movement Edited by one of the founders and lead investigator of the Green500 list, The Green Computing Book: Tackling Energy Efficiency at Large Scale explores seminal research in large-scale green computing. It begins with low-level, hardware-based approaches and then traverses up the software stack with increasingly higher-level, software-based approaches. In the first chapter, the IBM Blue Gene team illustrates how to improve the energy efficiency of a supercomputer by an order of magnitude without any system performance loss in parallelizable applications. The next few chapters explain how to enhance the energy efficiency of a large-scale computing system via compiler-directed energy optimizations, an adaptive run-time system, and a general prediction performance framework. The book then explores the interactions between energy management and reliability and describes storage system organization that maximizes energy efficiency and reliability. It also addresses the need for coordinated power control across different layers and covers demand response policies in computing centers. The final chapter assesses the impact of servers on data center costs.

Computational Intelligence In Sustainable Computing And Optimization

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Author : Balamurugan Balusamy
language : en
Publisher: Elsevier
Release Date : 2024-10-08

Computational Intelligence In Sustainable Computing And Optimization written by Balamurugan Balusamy and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-08 with Computers categories.

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. - Presents computational, intelligence–based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management - Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources - Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and their applications for sustainable computing

Advanced Computational Techniques For Sustainable Computing

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Author : Megha Rathi
language : en
Publisher: CRC Press
Release Date : 2022-07-25

Advanced Computational Techniques For Sustainable Computing written by Megha Rathi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-25 with Computers categories.

Advanced Computational Techniques for Sustainable Computing is considered multi-disciplinary field encompassing advanced computational techniques across several domain, including, Computer Science, Statistical Computation and Electronics Engineering. The core idea of sustainable computing is to deploy algorithms, models, policies and protocols to improve energy efficiency and management of resources, enhancing ecological balance, biological sustenance and other services on societal contexts. The book offers a comprehensive coverage of some of the most essential topics: It provides an insight on building smart sustainable solutions. Includes details of applying mining, learning, IOT and sensor-based techniques for sustainable computing. Entails data extraction from various sources followed with pre-processing of data, and how to make effective use of extracted data for application-based research. Involves practical usage of data analytic language, including R, Python, etc. for improving sustainable services offered by multi-disciplinary domains. Encompasses comparison and analysis of recent technologies and trends. Includes development of smart models for information gain and effective decision making with visualization. The readers would get acquainted with the utilization of massive data sets for intelligent mining and processing. It includes the integration of data mining techniques for effective decision-making in the social, economic, and global environmental domains to achieve sustainability. The implementation of computational frameworks can be accomplished using open-source software for the building of resource-efficient models. The content of the book demonstrates the usage of data science and the internet of things for the advent of smart and realistic solutions for attaining sustainability.

Big Data Science And Analytics For Smart Sustainable Urbanism

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Author : Simon Elias Bibri
language : en
Publisher: Springer
Release Date : 2019-05-30

Big Data Science And Analytics For Smart Sustainable Urbanism written by Simon Elias Bibri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Social Science categories.

We are living at the dawn of what has been termed ‘the fourth paradigm of science,’ a scientific revolution that is marked by both the emergence of big data science and analytics, and by the increasing adoption of the underlying technologies in scientific and scholarly research practices. Everything about science development or knowledge production is fundamentally changing thanks to the ever-increasing deluge of data. This is the primary fuel of the new age, which powerful computational processes or analytics algorithms are using to generate valuable knowledge for enhanced decision-making, and deep insights pertaining to a wide variety of practical uses and applications. This book addresses the complex interplay of the scientific, technological, and social dimensions of the city, and what it entails in terms of the systemic implications for smart sustainable urbanism. In concrete terms, it explores the interdisciplinary and transdisciplinary field of smart sustainable urbanism and the unprecedented paradigmatic shifts and practical advances it is undergoing in light of big data science and analytics. This new era of science and technology embodies an unprecedentedly transformative and constitutive power—manifested not only in the form of revolutionizing science and transforming knowledge, but also in advancing social practices, producing new discourses, catalyzing major shifts, and fostering societal transitions. Of particular relevance, it is instigating a massive change in the way both smart cities and sustainable cities are studied and understood, and in how they are planned, designed, operated, managed, and governed in the face of urbanization. This relates to what has been dubbed data-driven smart sustainable urbanism, an emerging approach based on a computational understanding of city systems and processes that reduces urban life to logical and algorithmic rules and procedures, while also harnessing urban big data to provide a more holisticand integrated view or synoptic intelligence of the city. This is increasingly being directed towards improving, advancing, and maintaining the contribution of both sustainable cities and smart cities to the goals of sustainable development. This timely and multifaceted book is aimed at a broad readership. As such, it will appeal to urban scientists, data scientists, urbanists, planners, engineers, designers, policymakers, philosophers of science, and futurists, as well as all readers interested in an overview of the pivotal role of big data science and analytics in advancing every academic discipline and social practice concerned with data–intensive science and its application, particularly in relation to sustainability.

Big Data Analytics For Sustainable Computing

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