Big Data In Energy Economics

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Big Data In Energy Economics

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Author : Hui Liu
language : en
Publisher: Springer Nature
Release Date : 2022-02-08

Big Data In Energy Economics written by Hui Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-08 with Business & Economics categories.

This book combines energy economics and big data modeling analysis in energy conversion and management and comprehensively introduces the relevant theories, key technologies, and application examples of the smart energy economy. With the help of time series big data modeling results, energy economy managers develop reasonable and feasible pricing mechanisms of electricity price and improve the absorption capacity of the power grid. In addition, they also carry out scientific power equipment scheduling and cost–benefit analysis according to the results of data mining, so as to avoid the loss caused by accidental damage of equipment. Energy users adjust their power consumption behavior through the modeling results provided and achieve the effect of energy saving and emission reduction while reasonably reducing the electricity expenditure. This book provides an important reference for professionals in related fields such as smart energy, smart economy, energy Internet, artificial intelligence, energy economics and policy.

Big Data In Energy Economics

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Author : 刘辉
language : en
Publisher:
Release Date : 2022

Big Data In Energy Economics written by 刘辉 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Big data categories.

Big Data Mining For Climate Change

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Author : Zhihua Zhang
language : en
Publisher: Elsevier
Release Date : 2019-11-20

Big Data Mining For Climate Change written by Zhihua Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Science categories.

Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation’s big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy. Provides a step-by-step guide for applying big data mining tools to climate and environmental research Presents a comprehensive review of theory and algorithms of big data mining for climate change Includes current research in climate and environmental science as it relates to using big data algorithms

Big Data For Twenty First Century Economic Statistics

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Author : Katharine G. Abraham
language : en
Publisher: University of Chicago Press
Release Date : 2022-03-11

Big Data For Twenty First Century Economic Statistics written by Katharine G. Abraham and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Business & Economics categories.

Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Smart Grids And Big Data Analytics For Smart Cities

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Author : Chun Sing Lai
language : en
Publisher: Springer Nature
Release Date : 2020-10-31

Smart Grids And Big Data Analytics For Smart Cities written by Chun Sing Lai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Technology & Engineering categories.

This book provides a comprehensive introduction to different elements of smart city infrastructure - smart energy, smart water, smart health, and smart transportation - and how they work independently and together. Theoretical development and practical applications are presented, along with related standards, recommended practices, and professional guidelines. Throughout the book, diagrams and case studies are provided that demonstrate the systems presented, and extensive use of scenarios helps readers better grasp how smart grids, the Internet of Things, big data analytics, and trading models can improve road safety, healthcare, smart water management, and a low-carbon economy. A must-read for practicing engineers, consultants, regulators, utility operators, and environmentalists involved in smart city development, the book will also appeal to city planners and designers, as well as upper-level undergraduate and graduate students studying energy, environmental science, technology, economics, signal processing, information science, and power engineering.

Energy And Analytics

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Author : John J. McGowan
language : en
Publisher: CRC Press
Release Date : 2020-11-26

Energy And Analytics written by John J. McGowan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-26 with Business & Economics categories.

This book details how to leverage big data style analytics to manage and coordinate the key issues in both energy supply and demand. It presents a detailed explanation of the underlying systems technology that enables big data in buildings and how this technology provides added cost benefit from efficiency, onsite solar, and electricity markets. It is a primer on Building Automation Systems Standards, web services and electricity markets and programs plus a complete tutorial on energy analytics hardware, software, and Internet-enabled offerings that energy managers must understand today.

Big Data Analytics In Future Power Systems

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Author : Ahmed F. Zobaa
language : en
Publisher: CRC Press
Release Date : 2018

Big Data Analytics In Future Power Systems written by Ahmed F. Zobaa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Big data categories.

Power systems are increasingly collecting large amounts of data due to the expansion of the Internet of Things into power grids. In a smart grids scenario, a huge number of intelligent devices will be connected with almost no human intervention characterizing a machine-to-machine scenario, which is one of the pillars of the Internet of Things. The book characterizes and evaluates how the emerging growth of data in communications networks applied to smart grids will impact the grid efficiency and reliability. Additionally, this book discusses the various security concerns that become manifest with Big Data and expanded communications in power grids. Provide a general description and definition of big data, which has been gaining significant attention in the research community. Introduces a comprehensive overview of big data optimization methods in power system. Reviews the communication devices used in critical infrastructure, especially power systems; security methods available to vet the identity of devices; and general security threats in CI networks. Presents applications in power systems, such as power flow and protection. Reviews electricity theft concerns and the wide variety of data-driven techniques and applications developed for electricity theft detection.

Data Science And Big Data An Environment Of Computational Intelligence

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Author : Witold Pedrycz
language : en
Publisher: Springer
Release Date : 2017-03-21

Data Science And Big Data An Environment Of Computational Intelligence written by Witold Pedrycz and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-21 with Technology & Engineering categories.

This book presents a comprehensive and up-to-date treatise of a range of methodological and algorithmic issues. It also discusses implementations and case studies, identifies the best design practices, and assesses data analytics business models and practices in industry, health care, administration and business.Data science and big data go hand in hand and constitute a rapidly growing area of research and have attracted the attention of industry and business alike. The area itself has opened up promising new directions of fundamental and applied research and has led to interesting applications, especially those addressing the immediate need to deal with large repositories of data and building tangible, user-centric models of relationships in data. Data is the lifeblood of today’s knowledge-driven economy.Numerous data science models are oriented towards end users and along with the regular requirements for accuracy (which are present in any modeling), come the requirements for ability to process huge and varying data sets as well as robustness, interpretability, and simplicity (transparency). Computational intelligence with its underlying methodologies and tools helps address data analytics needs.The book is of interest to those researchers and practitioners involved in data science, Internet engineering, computational intelligence, management, operations research, and knowledge-based systems.

Big Data

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Author : Viktor Mayer-Schönberger
language : en
Publisher: Harper Business
Release Date : 2014

Big Data written by Viktor Mayer-Schönberger and has been published by Harper Business this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computers categories.

Explores the idea of big data, which refers to our newfound ability to crunch vast amounts of information, analyze it instantly, and draw profound and surprising conclusions from it.

Application Of Big Data Deep Learning Machine Learning And Other Advanced Analytical Techniques In Environmental Economics And Policy

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Author : Tsun Se Cheong
language : en
Publisher: Frontiers Media SA
Release Date : 2022-07-25

Application Of Big Data Deep Learning Machine Learning And Other Advanced Analytical Techniques In Environmental Economics And Policy written by Tsun Se Cheong and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-25 with Technology & Engineering categories.