Advances of Machine Learning in Clean Energy and the Transportation Industry - 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 Advances of Machine Learning in Clean Energy and the Transportation Industry write by Pandian Vasant. This book was released on 2021-11-30. Advances of Machine Learning in Clean Energy and the Transportation Industry available in PDF, EPUB and Kindle. 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, optimization 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 optimization, 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.
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies - 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 Developments by Artificial Intelligence and Machine Learning for Renewable Energies write by Krishna Kumar. This book was released on 2022-03-18. Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies available in PDF, EPUB and Kindle. 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
Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems
Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems - 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 Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems write by Yuekuan Zhou. This book was released on 2023-11-20. Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems available in PDF, EPUB and Kindle. Advances in Digitalization and Machine Learning for Integrated Building-Transportation Energy Systems examines the combined impact of buildings and transportation systems on energy demand and use. With a strong focus on AI and machine learning approaches, the book comprehensively discusses each part of the energy life cycle, considering source, grid, demand, storage, and usage. Opening with an introduction to smart buildings and intelligent transportation systems, the book presents the fundamentals of AI and its application in renewable energy sources, alongside the latest technological advances. Other topics presented include building occupants’ behavior and vehicle driving schedule with demand prediction and analysis, hybrid energy storages in buildings with AI, smart grid with energy digitalization, and prosumer-based P2P energy trading. The book concludes with discussions on blockchain technologies, IoT in smart grid operation, and the application of big data and cloud computing in integrated smart building-transportation energy systems. A smart and flexible energy system is essential for reaching Net Zero whilst keeping energy bills affordable. This title provides critical information to students, researchers and engineers wanting to understand, design, and implement flexible energy systems to meet the rising demand in electricity. Introduces spatiotemporal energy sharing with new energy vehicles and human-machine interactions Discusses the potential for electrification and hydrogenation in integrated building-transportation systems for sustainable development Highlights key topics related to traditional energy consumers, including peer-to-peer energy trading and cost-benefit business models
Machine Learning and Computer Vision for Renewable Energy
Machine Learning and Computer Vision for Renewable Energy - 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 Machine Learning and Computer Vision for Renewable Energy write by Acharjya, Pinaki Pratim. This book was released on 2024-05-01. Machine Learning and Computer Vision for Renewable Energy available in PDF, EPUB and Kindle. As the world grapples with the urgent need for sustainable energy solutions, the limitations of traditional approaches to renewable energy forecasting become increasingly evident. The demand for more accurate predictions in net load forecasting, line loss predictions, and the seamless integration of hybrid solar and battery storage systems is more critical than ever. In response to this challenge, advanced Artificial Intelligence (AI) techniques are emerging as a solution, promising to revolutionize the renewable energy landscape. Machine Learning and Computer Vision for Renewable Energy presents a deep exploration of AI modeling, analysis, performance prediction, and control approaches dedicated to overcoming the pressing issues in renewable energy systems. Transitioning from the complexities of energy prediction to the promise of advanced technology, the book sets its sights on the game-changing potential of computer vision (CV) in the realm of renewable energy. Amidst the struggle to enhance sustainability across industries, CV technology emerges as a powerful ally, collecting invaluable data from digital photos and videos. This data proves instrumental in achieving better energy management, predicting factors affecting renewable energy, and optimizing overall sustainability. Readers, including researchers, academicians, and students, will find themselves immersed in a comprehensive understanding of the AI approaches and CV methodologies that hold the key to resolving the challenges faced by renewable energy systems.
AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications
AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications - 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 AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications write by Angalaeswari, S.. This book was released on 2023-02-03. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications available in PDF, EPUB and Kindle. Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
