Decision Analytics for Sustainable Development in Smart Society 5.0 - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Decision Analytics for Sustainable Development in Smart Society 5.0 write by Vikram Bali. This book was released on 2022-06-23. Decision Analytics for Sustainable Development in Smart Society 5.0 available in PDF, EPUB and Kindle. This book covers sustainable development in smart society’s 5.0 using data analytics. The data analytics is the approach of integrating diversified heterogeneous data for predictive analysis to accredit innovation, decision making, business analysis, and strategic decision making. The data science brings together the research in the field of data analytics, online information analytics, and big data analytics to synthesize issues, challenges, and opportunities across smart society 5.0. Accordingly, the book offers an interesting and insightful read for researchers in the areas of decision analytics, cognitive analytics, big data analytics, visual analytics, text analytics, spatial analytics, risk analytics, graph analytics, predictive analytics, and analytics-enabled applications.
Introduction to Sustainability Analytics
Introduction to Sustainability Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Sustainability Analytics write by Raghavan (Ram) Ramanan. This book was released on 2017. Introduction to Sustainability Analytics available in PDF, EPUB and Kindle. "Society must consider the impacts of climate change and the subsequent move toward public and corporate environmental sustainability. This book will merge corporate and public sector perspectives on sustainable development with regard to business and engineering approaches. Sustainability metrics and indices will be addressed using practical examples. It will also introduce and expand on economic issues, environmental concerns, social concerns, and ethics. It will address decision analysis and sustainability analytics in the context of the business value of corporate social responsibility, public policy, life-cycle assessment, climate change and energy, and a circular economy."--Provided by publisher.
Sustainable Development Through Data Analytics and Innovation
Sustainable Development Through Data Analytics and Innovation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Sustainable Development Through Data Analytics and Innovation write by Jorge Marx Gómez. This book was released on 2022-09-26. Sustainable Development Through Data Analytics and Innovation available in PDF, EPUB and Kindle. Sustainable development is based on the idea that societies should advance without compromising their future development requirements. This book explores how the application of data analytics and digital technologies can ensure that development changes are executed on the basis of factual data and information. It addresses how innovations that rely on digital technologies can support sustainable development across all sectors and all social, economic, and environmental aspects and help us achieve the Sustainable Development Goals (SDGs). The book also highlights techniques, processes, models, tools, and practices used to achieve sustainable development through data analysis. The various topics covered in this book are critically evaluated, not only theoretically, but also from an application perspective. It will be of interest to researchers and students, especially those in the fields of applied data analytics, business intelligence and knowledge management.
Smart Sustainable Cities of the Future
Smart Sustainable Cities of the Future - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Smart Sustainable Cities of the Future write by Simon Elias Bibri. This book was released on 2018-02-24. Smart Sustainable Cities of the Future available in PDF, EPUB and Kindle. 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.
Computational Intelligent Data Analysis for Sustainable Development
Computational Intelligent Data Analysis for Sustainable Development - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Computational Intelligent Data Analysis for Sustainable Development write by Ting Yu. This book was released on 2013-04-04. Computational Intelligent Data Analysis for Sustainable Development available in PDF, EPUB and Kindle. Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems. With a focus on integrated sustainability analysis, the book presents a large-scale quadratic programming algorithm to expand high-resolution input-output tables from the national scale to the multinational scale to measure the carbon footprint of the entire trade supply chain. It also quantifies the error or dispersion between different reclassification and aggregation schemas, revealing that aggregation errors have a high concentration over specific regions and sectors. The book summarizes the latest contributions of the data analysis community to climate change research. A profuse amount of climate data of various types is available, providing a rich and fertile playground for future data mining and machine learning research. The book also pays special attention to several critical challenges in the science of climate extremes that are not handled by the current generation of climate models. It discusses potential conceptual and methodological directions to build a close integration between physical understanding, or physics-based modeling, and data-driven insights. The book then covers the conservation of species and ecologically valuable land. A case study on the Pennsylvania Dirt and Gravel Roads Program demonstrates that multiple-objective linear programming is a more versatile and efficient approach than the widely used benefit targeting selection process. Moving on to renewable energy and the need for smart grids, the book explores how the ongoing transformation to a sustainable energy system of renewable sources leads to a paradigm shift from demand-driven generation to generation-driven demand. It shows how to maximize renewable energy as electricity by building a supergrid or mixing renewable sources with demand management and storage. It also presents intelligent data analysis for real-time detection of disruptive events from power system frequency data collected using an existing Internet-based frequency monitoring network as well as evaluates a set of computationally intelligent techniques for long-term wind resource assessment. In addition, the book gives an example of how temporal and spatial data analysis tools are used to gather knowledge about behavioral data and address important social problems such as criminal offenses. It also applies constraint logic programming to a planning problem: the environmental and social impact assessment of the regional energy plan of the Emilia-Romagna region of Italy. Sustainable development problems, such as global warming, resource shortages, global species loss, and pollution, push researchers to create powerful data analysis approaches that analysts can then use to gain insight into these issues to support rational decision making. This volume shows both the data analysis and sustainable development communities how to use intelligent data analysis tools to address practical problems and encourages researchers to develop better methods.
