Machine Learning Applications For Intelligent Energy Management

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Machine Learning Applications for Intelligent Energy Management

Author : Haris Doukas
Publisher : Springer
ISBN 13 : 9783031479083
Total Pages : 0 pages
Book Rating : 4.4/5 (79 download)

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Book Synopsis Machine Learning Applications for Intelligent Energy Management by : Haris Doukas

Download or read book Machine Learning Applications for Intelligent Energy Management written by Haris Doukas and published by Springer. This book was released on 2024-02-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: As carbon dioxide (CO2) emissions and other greenhouse gases constantly rise and constitute the main contributor to climate change, temperature rise and global warming, artificial intelligence, big data, Internet of things, and blockchain technologies are enlisted to help enforce energy transition and transform the entire energy sector. The book at hand presents state-of-the-art developments in artificial intelligence-empowered analytics of energy data and artificial intelligence-empowered application development. Topics covered include a presentation of the various stakeholders in the energy sector and their corresponding required analytic services, such as state-of-the-art machine learning, artificial intelligence, and optimization models and algorithms tailored for a series of demanding energy problems and aiming at providing optimal solutions under specific constraints. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.

Applications of AI and IOT in Renewable Energy

Author : Rabindra Nath Shaw
Publisher : Academic Press
ISBN 13 : 0323984010
Total Pages : 248 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Applications of AI and IOT in Renewable Energy by : Rabindra Nath Shaw

Download or read book Applications of AI and IOT in Renewable Energy written by Rabindra Nath Shaw and published by Academic Press. This book was released on 2022-02-09 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications of AI and IOT in Renewable Energy provides a future vision of unexplored areas and applications for Artificial Intelligence and Internet of Things in sustainable energy systems. The ideas presented in this book are backed up by original, unpublished technical research results covering topics like smart solar energy systems, intelligent dc motors and energy efficiency study of electric vehicles. In all these areas and more, applications of artificial intelligence methods, including artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above in hybrid systems are included. This book is designed to assist with developing low cost, smart and efficient solutions for renewable energy systems and is intended for researchers, academics and industrial communities engaged in the study and performance prediction of renewable energy systems. - Includes future applications of AI and IOT in renewable energy - Based on case studies to give each chapter real-life context - Provides advances in renewable energy using AI and IOT with technical detail and data

Machine Learning for Energy Systems

Author : Denis Sidorov
Publisher : MDPI
ISBN 13 : 3039433822
Total Pages : 272 pages
Book Rating : 4.0/5 (394 download)

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Book Synopsis Machine Learning for Energy Systems by : Denis Sidorov

Download or read book Machine Learning for Energy Systems written by Denis Sidorov and published by MDPI. This book was released on 2020-12-08 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.

Intelligent Renewable Energy Systems

Author : Neeraj Priyadarshi
Publisher : John Wiley & Sons
ISBN 13 : 1119786274
Total Pages : 484 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Intelligent Renewable Energy Systems by : Neeraj Priyadarshi

Download or read book Intelligent Renewable Energy Systems written by Neeraj Priyadarshi and published by John Wiley & Sons. This book was released on 2022-01-19 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTELLIGENT RENEWABLE ENERGY SYSTEMS This collection of papers on artificial intelligence and other methods for improving renewable energy systems, written by industry experts, is a reflection of the state of the art, a must-have for engineers, maintenance personnel, students, and anyone else wanting to stay abreast with current energy systems concepts and technology. Renewable energy is one of the most important subjects being studied, researched, and advanced in today’s world. From a macro level, like the stabilization of the entire world’s economy, to the micro level, like how you are going to heat or cool your home tonight, energy, specifically renewable energy, is on the forefront of the discussion. This book illustrates modelling, simulation, design and control of renewable energy systems employed with recent artificial intelligence (AI) and optimization techniques for performance enhancement. Current renewable energy sources have less power conversion efficiency because of its intermittent and fluctuating behavior. Therefore, in this regard, the recent AI and optimization techniques are able to deal with data ambiguity, noise, imprecision, and nonlinear behavior of renewable energy sources more efficiently compared to classical soft computing techniques. This book provides an extensive analysis of recent state of the art AI and optimization techniques applied to green energy systems. Subsequently, researchers, industry persons, undergraduate and graduate students involved in green energy will greatly benefit from this comprehensive volume, a must-have for any library. Audience Engineers, scientists, managers, researchers, students, and other professionals working in the field of renewable energy.

Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles

Author : Teng Liu
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681736195
Total Pages : 99 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles by : Teng Liu

Download or read book Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles written by Teng Liu and published by Morgan & Claypool Publishers. This book was released on 2019-09-03 with total page 99 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles. Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application. In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.

Application of Machine Learning and Deep Learning Methods to Power System Problems

Author : Morteza Nazari-Heris
Publisher : Springer Nature
ISBN 13 : 3030776964
Total Pages : 391 pages
Book Rating : 4.0/5 (37 download)

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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.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

Author : Krishna Kumar
Publisher : Academic Press
ISBN 13 : 0323914284
Total Pages : 418 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies by : Krishna Kumar

Download or read book Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies written by Krishna Kumar and published by Academic Press. This book was released on 2022-03-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. - Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment - Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum - Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

Energy Conversion and Management

Author : Giovanni Petrecca
Publisher : Springer
ISBN 13 : 3319065602
Total Pages : 350 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Energy Conversion and Management by : Giovanni Petrecca

Download or read book Energy Conversion and Management written by Giovanni Petrecca and published by Springer. This book was released on 2014-08-07 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overall view of energy conversion and management in industry and in buildings by following the streams of energy from the site boundaries to the end users. Written for an audience of both practitioners and faculty/students, Energy Conversion and Management: Principles and Applications presents general principles of energy conversion and energy sources, both traditional and renewable, in a broad range of facilities such as electrical substations, boiler plants, heat and power plants, electrical networks, thermal fluid distributions lines and insulations, pumps and fans, air compressor systems, cooling plants, HVAC, lighting, and heat recovery plants. The book also examines principles of energy auditing and accounting, the correlation between energy and environment, and includes detail on the economic analysis of energy saving investment and education in the field of energy. This book also: · Explores a broad array of power generation and distribution facilities around the concept of energy conversion, from traditional and renewable sources, correlating many apparently disparate topics · Elucidates fundamental formulas and information-rich figures to help readers in solving any practical energy conversion problems · Emphasizes a holistic perspective on energy conversion and management with a vision of each application as a system beyond its individual elements · Includes a set of Key Performance Index using metrics applicable to energy systems brought into operation over the past 30 years · Gives a set of basic formulas and data that are the essentials of energy conversion and that everybody involved in these fields should perfectly know · Adopts a writing style accessible to technicians and managers in the field of energy conversion while maintaining sufficient rigor and coverage for engineers

14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019)

Author : Francisco Martínez Álvarez
Publisher : Springer
ISBN 13 : 3030200558
Total Pages : 617 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) by : Francisco Martínez Álvarez

Download or read book 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019) written by Francisco Martínez Álvarez and published by Springer. This book was released on 2019-04-30 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes 57 papers presented at the SOCO 2019 conference held in the historic city of Seville (Spain), in May 2019. Soft computing represents a set of computational techniques in machine learning, computer science and various engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. The selection of papers was extremely rigorous in order to maintain the high quality of the conference, which featured a number of special sessions, including sessions on: Soft Computing Methods in Manufacturing and Management Systems; Soft Computing Applications in the Field of Industrial and Environmental Enterprises; Optimization, Modeling and Control by Soft Computing Techniques; and Soft Computing in Aerospace, Mechanical and Civil Engineering: New methods and Industrial Applications.

Internet of Energy for Smart Cities

Author : Anish Jindal
Publisher : CRC Press
ISBN 13 : 1000410986
Total Pages : 323 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Internet of Energy for Smart Cities by : Anish Jindal

Download or read book Internet of Energy for Smart Cities written by Anish Jindal and published by CRC Press. This book was released on 2021-07-19 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning approaches has the capability to learn and adapt to the constantly evolving demands of large Internet-of-energy (IoE) network. The focus of this book is on using the machine learning approaches to present various solutions for IoE network in smart cities to solve various research gaps such as demand response management, resource management and effective utilization of the underlying ICT network. It provides in-depth knowledge to build the technical understanding for the reader to pursue various research problems in this field. Moreover, the example problems in smart cities and their solutions using machine learning are provided as relatable to the real-life scenarios. Aimed at Graduate Students, Researchers in Computer Science, Electrical Engineering, Telecommunication Engineering, Internet of Things, Machine Learning, Green computing, Smart Grid, this book: Covers all aspects of Internet of Energy (IoE) and smart cities including research problems and solutions. Points to the solutions provided by machine learning to optimize the grids within a smart city set-up. Discusses relevant IoE design principles and architecture. Helps to automate various services in smart cities for energy management. Includes case studies to show the effectiveness of the discussed schemes.

Green Internet of Things and Machine Learning

Author : Roshani Raut
Publisher : John Wiley & Sons
ISBN 13 : 1119793122
Total Pages : 279 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Green Internet of Things and Machine Learning by : Roshani Raut

Download or read book Green Internet of Things and Machine Learning written by Roshani Raut and published by John Wiley & Sons. This book was released on 2022-01-10 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health Economics and Financing Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment. The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier. Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare. Audience The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

Smart City

Author : Renata Paola Dameri
Publisher : Springer
ISBN 13 : 3319061607
Total Pages : 239 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Smart City by : Renata Paola Dameri

Download or read book Smart City written by Renata Paola Dameri and published by Springer. This book was released on 2014-06-26 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a comprehensive overview of the various aspects for the development of smart cities from a European perspective. It presents both theoretical concepts as well as empirical studies and cases of smart city programs and their capacity to create value for citizens. The contributions in this book are a result of an increasing interest for this topic, supported by both national governments and international institutions. The book offers a large panorama of the most important aspects of smart cities evolution and implementation. It compares European best practices and analyzes how smart projects and programs in cities could help to improve the quality of life in the urban space and to promote cultural and economic development.

Advances of Machine Learning in Clean Energy and the Transportation Industry

Author : Pandian Vasant
Publisher :
ISBN 13 : 9781685072117
Total Pages : 0 pages
Book Rating : 4.0/5 (721 download)

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Book Synopsis Advances of Machine Learning in Clean Energy and the Transportation Industry by : Pandian Vasant

Download or read book Advances of Machine Learning in Clean Energy and the Transportation Industry written by Pandian Vasant and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest research in the field of machine learning, discussing the real-world application problems associated with new innovative renewable energy methodologies as well as cutting edge technologies in the transport industry. The requirements and demands of problem solving have been increasing exponentially, and new artificial intelligence and machine learning technologies have reduced the scope of data coverage worldwide. Recent advances in data technology (DT) have contributed to reducing the gaps in the coverage of domains around the globe. Attention to clean energy in recent decades has been growing exponentially. This is mainly due to a decrease in the cost of both installed capacity of converters and a decrease in the cost of generated energy. Such successes were achieved thanks to the improvement of modern technologies for the production of converters, an increase in the efficiency of using incoming energy, optimisation of the operation of converters and analysis of data obtained during the operation of systems with the possibility of planning production. The use of clean energy plays an important role in the transportation industry, where technologies are also being improved from year to year - the transportation industry is growing, and machinery and systems are becoming more autonomous and robotic, where it is no longer possible to do without complex intelligent computing, machine learning optimisation, planning and working with large amounts of data. The book is a valuable reference work for researchers in the fields of renewable energy, computer science and engineering with a particular focus on machine learning and intelligent optimization as well as for postgraduates, managers, economists and decision makers, policy makers, government officials, industrialists and practicing scientists and engineers as well compassionate global decision makers. Topics include: Machine learning, Quantum Optimization, Modern Technology in Transport Industry, Innovative Technologies in Transport Education, Systems Based on Renewable Energy Conversion, Business Process Models and Applications in Renewable Energy, Clean Energy, and Climate Change.

Machine Learning: Concepts, Methodologies, Tools and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
ISBN 13 : 1609608194
Total Pages : 2174 pages
Book Rating : 4.6/5 (96 download)

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Book Synopsis Machine Learning: Concepts, Methodologies, Tools and Applications by : Management Association, Information Resources

Download or read book Machine Learning: Concepts, Methodologies, Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2011-07-31 with total page 2174 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe

Renewable Energy for Smart and Sustainable Cities

Author : Mustapha Hatti
Publisher : Springer
ISBN 13 : 303004789X
Total Pages : 571 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Renewable Energy for Smart and Sustainable Cities by : Mustapha Hatti

Download or read book Renewable Energy for Smart and Sustainable Cities written by Mustapha Hatti and published by Springer. This book was released on 2018-11-23 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features cutting-edge research presented at the second international conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES2018, held on 24–26 November 2018, at the High School of Commerce, ESC-Koléa in Tipaza, Algeria. Today, the fundamental challenge of integrating renewable energies into the design of smart cities is more relevant than ever. While based on the advent of big data and the use of information and communication technologies, smart cities must now respond to cross-cutting issues involving urban development, energy and environmental constraints; further, these cities must also explore how they can integrate more sustainable energies. Sustainable energies are a major determinant of smart cities’ longevity. From an environmental and technological standpoint, these energies offer an optimal power supply to the electric network while creating significantly less pollution. This requires flexibility, i.e., the availability of supply and demand. The end goal of any smart city is to improve the quality of life for all citizens (both in the city and in the countryside) in a way that is sustainable and respectful of the environment. This book encourages the reader to engage in the preservation of our environment, every moment, every day, so as to help build a clean and healthy future, and to think of the future generations who will one day inherit our planet. Further, it equips those whose work involves energy systems and those engaged in modelling artificial intelligence to combine their expertise for the benefit of the scientific community and humanity as a whole.

Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles

Author : Teng Liu
Publisher : Springer Nature
ISBN 13 : 3031015037
Total Pages : 90 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles by : Teng Liu

Download or read book Reinforcement Learning-Enabled Intelligent Energy Management for Hybrid Electric Vehicles written by Teng Liu and published by Springer Nature. This book was released on 2022-06-01 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt: Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles. Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application. In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.

Machine Learning and Intelligent Communications

Author : Mingxiang Guan
Publisher : Springer Nature
ISBN 13 : 3030667855
Total Pages : 538 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Machine Learning and Intelligent Communications by : Mingxiang Guan

Download or read book Machine Learning and Intelligent Communications written by Mingxiang Guan and published by Springer Nature. This book was released on 2021-01-23 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed post-conference proceedings of the 5th International Conference on Machine Learning and Intelligent Communications, MLICOM 2020, held in Shenzhen, China, in September 2020. Due to COVID-19 pandemic the conference was held virtually. The 55 revised full papers were carefully selected from 133 submissions. The papers are organized thematically in intelligent resource ( spectrum, power) allocation schemes; applications of neural network and deep learning; decentralized learning for wireless communication systems; intelligent antennas design and dynamic configuration; intelligent communications; intelligent positioning and navigation systems; smart unmanned vehicular technology; intelligent space and terrestrial integrated networks; machine learning algorithm and Intelligent networks.