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Forecasting Electricity Prices With Machine Learning
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Book Synopsis Managing Energy Risk by : Markus Burger
Download or read book Managing Energy Risk written by Markus Burger and published by John Wiley & Sons. This book was released on 2008-04-30 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical techniques for trading and risk management. Managing Energy Risk closes the gap between modern techniques from financial mathematics and the practical implementation for trading and risk management. It takes a multi-commodity approach that covers the mutual influences of the markets for fuels, emission certificates, and power. It includes many practical examples and covers methods from financial mathematics as well as economics and energy-related models.
Book Synopsis Innovative Mobile and Internet Services in Ubiquitous Computing by : Leonard Barolli
Download or read book Innovative Mobile and Internet Services in Ubiquitous Computing written by Leonard Barolli and published by Springer. This book was released on 2019-06-18 with total page 950 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the latest research findings, methods and techniques, as well as challenges and solutions related to Ubiquitous and Pervasive Computing (UPC). In this regard, it employs both theoretical and practical perspectives, and places special emphasis on innovative, mobile and internet services. With the proliferation of wireless technologies and electronic devices, there is a rapidly growing interest in Ubiquitous and Pervasive Computing (UPC). UPC makes it possible to create a human-oriented computing environment in which computer chips are embedded in everyday objects and interact with the physical world. Through UPC, people can remain online even while underway, thus enjoying nearly permanent access to their preferred services. Though it has a great potential to revolutionize our lives, UPC also poses a number of new research challenges.
Book Synopsis Energy Pricing Models by : Marcel Prokopczuk
Download or read book Energy Pricing Models written by Marcel Prokopczuk and published by Palgrave Macmillan. This book was released on 2014-12-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Following the liberalization of global energy markets, the world has witnessed a substantial growth in energy commodity trading. Moreover, prices and volatilities have significantly increased, partly due to geopolitical crises, but mostly resulting from increased participation of financial investors. Such newfound interest in energy markets has spawned greater demand for state-of-the-art models and methods necessary to understand the challenges related to trading and risk management. Energy Pricing Models showcases original cutting-edge research to best illustrate the latest advances and future implications of trading in energy markets. Prokopczuk assembles an all-star team of leading academics and practitioners in order to provide a well-balanced analysis of the topic. This work is required reading for market practitioners wishing to gain greater insight into the field, as well as academics and researchers interested in learning more about the latest developments from an applied perspective.
Book Synopsis Intelligent Decision Technologies by : Rui Neves-Silva
Download or read book Intelligent Decision Technologies written by Rui Neves-Silva and published by Springer. This book was released on 2016-10-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the 57 papers accepted for presentation at the Seventh KES International Conference on Intelligent Decision Technologies (KES-IDT 2015), held in Sorrento, Italy, in June 2015. The conference consists of keynote talks, oral and poster presentations, invited sessions and workshops on the applications and theory of intelligent decision systems and related areas. The conference provides an opportunity for the presentation and discussion of interesting new research results, promoting knowledge transfer and the generation of new ideas. The book will be of interest to all those whose work involves the development and application of intelligent decision systems.
Book Synopsis Web, Artificial Intelligence and Network Applications by : Leonard Barolli
Download or read book Web, Artificial Intelligence and Network Applications written by Leonard Barolli and published by Springer Nature. This book was released on 2020-03-30 with total page 1487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings book presents the latest research findings, and theoretical and practical perspectives on innovative methods and development techniques related to the emerging areas of Web computing, intelligent systems and Internet computing. The Web has become an important source of information, and techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play a key role in many of today's major Web applications, such as e-commerce and computer security. Moreover, Web services provide a new platform for enabling service-oriented systems. The emergence of large-scale distributed computing paradigms, such as cloud computing and mobile computing systems, has opened many opportunities for collaboration services, which are at the core of any information system. Artificial intelligence (AI) is an area of computer science that builds intelligent systems and algorithms that work and react like humans. AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning, and they have the potential to become enabling technologies for future intelligent networks. Research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences is vital for the future development and innovation of Web and Internet applications. Chapter "An Event-Driven Multi Agent System for Scalable Traffic Optimization" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Book Synopsis Modeling and Forecasting Electricity Loads and Prices by : Rafal Weron
Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by John Wiley & Sons. This book was released on 2007-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.
Book Synopsis Machine Learning and Information Processing by : Debabala Swain
Download or read book Machine Learning and Information Processing written by Debabala Swain and published by Springer Nature. This book was released on 2021-04-02 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers from the 2nd International Conference on Machine Learning and Information Processing (ICMLIP 2020), held at Vardhaman College of Engineering, Jawaharlal Nehru Technological University (JNTU), Hyderabad, India, from November 28 to 29, 2020. It presents the latest developments and technical solutions in the areas of advanced computing and data sciences, covering machine learning, artificial intelligence, human–computer interaction, IoT, deep learning, image processing and pattern recognition, and signal and speech processing.
Book Synopsis Handbook of Research on Advances in Data Analytics and Complex Communication Networks by : P. Venkata Krishna
Download or read book Handbook of Research on Advances in Data Analytics and Complex Communication Networks written by P. Venkata Krishna and published by IGI Global. This book was released on 2021 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This edited book discusses data analytics and complex communication networks and recommends new methodologies, system architectures, and other solutions to prevail over the current limitations faced by the field"--
Book Synopsis Web, Artificial Intelligence and Network Applications by : Leonard Barolli
Download or read book Web, Artificial Intelligence and Network Applications written by Leonard Barolli and published by Springer. This book was released on 2019-03-14 with total page 1217 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of Web Computing, Intelligent Systems and Internet Computing. As the Web has become a major source of information, techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play key roles in many of today’s prominent Web applications such as e-commerce and computer security. Moreover, the outcome of Web services delivers a new platform for enabling service-oriented systems. The emergence of large scale distributed computing paradigms, such as Cloud Computing and Mobile Computing Systems, has opened many opportunities for collaboration services, which are at the core of any Information System. Artificial Intelligence (AI) is an area of computer science that build intelligent systems and algorithms that work and react like humans. The AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning. They have the potential to become enabling technologies for the future intelligent networks. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences are very important for the future development and innovation of Web and Internet applications.
Book Synopsis Machine Learning for Time Series Forecasting with Python by : Francesca Lazzeri
Download or read book Machine Learning for Time Series Forecasting with Python written by Francesca Lazzeri and published by John Wiley & Sons. This book was released on 2020-12-03 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to apply the principles of machine learning to time series modeling with this indispensable resource Machine Learning for Time Series Forecasting with Python is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling. Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting. Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to: Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models’ performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting Machine Learning for Time Series Forecasting with Python is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts. Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.
Book Synopsis Innovative Mobile and Internet Services in Ubiquitous Computing by : Leonard Barolli
Download or read book Innovative Mobile and Internet Services in Ubiquitous Computing written by Leonard Barolli and published by Springer. This book was released on 2018-06-07 with total page 987 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research findings, methods and development techniques related to Ubiquitous and Pervasive Computing (UPC) as well as challenges and solutions from both theoretical and practical perspectives with an emphasis on innovative, mobile and internet services. With the proliferation of wireless technologies and electronic devices, there is a rapidly growing interest in Ubiquitous and Pervasive Computing (UPC). UPC makes it possible to create a human-oriented computing environment where computer chips are embedded in everyday objects and interact with physical world. It also allows users to be online even while moving around, providing them with almost permanent access to their preferred services. Along with a great potential to revolutionize our lives, UPC also poses new research challenges.
Book Synopsis Application of Machine Learning and Deep Learning Methods to Power System Problems by : Morteza Nazari-Heris
Download or read book Application of Machine Learning and Deep Learning Methods to Power System Problems written by Morteza Nazari-Heris and published by Springer Nature. This book was released on 2021-11-21 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.
Book Synopsis Deep Learning for Time Series Forecasting by : Jason Brownlee
Download or read book Deep Learning for Time Series Forecasting written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-08-30 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.
Book Synopsis Hybrid Evolutionary Algorithms by : Crina Grosan
Download or read book Hybrid Evolutionary Algorithms written by Crina Grosan and published by Springer. This book was released on 2007-08-29 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms". The chapters deal with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. Overall, the book has 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. The contributions were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed.
Book Synopsis Applied Operations Research and Financial Modelling in Energy by : André B. Dorsman
Download or read book Applied Operations Research and Financial Modelling in Energy written by André B. Dorsman and published by Springer Nature. This book was released on 2021-10-12 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector. This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University’s Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).
Book Synopsis Artificial Intelligence for Renewable Energy Systems by : Ajay Kumar Vyas
Download or read book Artificial Intelligence for Renewable Energy Systems written by Ajay Kumar Vyas and published by John Wiley & Sons. This book was released on 2022-03-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS Renewable energy systems, including solar, wind, biodiesel, hybrid energy, and other relevant types, have numerous advantages compared to their conventional counterparts. This book presents the application of machine learning and deep learning techniques for renewable energy system modeling, forecasting, and optimization for efficient system design. Due to the importance of renewable energy in today’s world, this book was designed to enhance the reader’s knowledge based on current developments in the field. For instance, the extraction and selection of machine learning algorithms for renewable energy systems, forecasting of wind and solar radiation are featured in the book. Also highlighted are intelligent data, renewable energy informatics systems based on supervisory control and data acquisition (SCADA); and intelligent condition monitoring of solar and wind energy systems. Moreover, an AI-based system for real-time decision-making for renewable energy systems is presented; and also demonstrated is the prediction of energy consumption in green buildings using machine learning. The chapter authors also provide both experimental and real datasets with great potential in the renewable energy sector, which apply machine learning (ML) and deep learning (DL) algorithms that will be helpful for economic and environmental forecasting of the renewable energy business. Audience The primary target audience includes research scholars, industry engineers, and graduate students working in renewable energy, electrical engineering, machine learning, information & communication technology.
Book Synopsis Advances in Electric Power and Energy Systems by : Mohamed E. El-Hawary
Download or read book Advances in Electric Power and Energy Systems written by Mohamed E. El-Hawary and published by John Wiley & Sons. This book was released on 2017-07-12 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial arenas. Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every maximization strategy. This book fills a gap in the literature on this increasingly important topic. Following an introductory chapter offering background information necessary for a full understanding of the forecasting issues covered, this book: Introduces advanced methods of time series forecasting, as well as neural networks Provides in-depth coverage of state-of-the-art power system load forecasting and electricity price forecasting Addresses river flow forecasting based on autonomous neural network models Deals with price forecasting in a competitive market Includes estimation of post-storm restoration times for electric power distribution systems Features contributions from world-renowned experts sharing their insights and expertise in a series of self-contained chapters Advances in Electric Power and Energy Systems is a valuable resource for practicing engineers, regulators, planners, and consultants working in or concerned with the electric power industry. It is also a must read for senior undergraduates, graduate students, and researchers involved in power system planning and operation.
