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This book aims to provide comprehensive insights into integrating modern engineering techniques such as machine learning (ML), artificial intelligence (AI), nanotechnology, digital twins, and the Internet of Things (IoT) with renewable energy. The book helps readers implement machine learning in sustainability and how these technologies can create better solutions. The book will also enrich readers by providing perspectives, methods, and inspiration for using machine learning to create a more sustainable and environmentally responsible world. Readers will find this book instrumental in broadening their understanding of machine learning applications in the energy sector. By delving into the concepts, perspectives, and skills presented, professionals can enhance their capacity to contribute meaningfully to the development and implementation of sustainable energy solutions.
List of contents
List of Contributors
Preface
Chapter 1 Green energy led sustainable development: Barriers and opportunities
Chapter 2 Machine Learning Driven Valorization of Organic Waste for Sustainable Bio-hydrogen Production
Chapter 3 Application of Neural Networks for Model-Prediction of Combustion and Emissions in Diesel Engines
Chapter 4 Enhanced Energy Storage with Hybrid Nanoparticles and Machine Learning for Energy Sustainability
Chapter 5 Model prediction of biomass gasification using support vector machines
Chapter 6 Role of machine learning techniques in modeling and optimization of biomass gasification parameters in downdraft gasifier
Chapter 7 Response surface methodology-based multi-attribute optimization of a hydrogen powered dual-fuel engines
Chapter 8 Addition of Nanoparticles in Biodiesel-Diesel Blends to Improve Engine Efficiency and Reduce Tailpipe Emission
Chapter 9 Hybrid Nanoparticles to improve solar based energy storage
Chapter 10 Application of artificial intelligence to model-predict the thermo-physical property of hybrid nanofluids
Chapter 11 Optimization of Nanofluids for Heat Exchangers: Dealing with Sedimentation and Pump Losses
Chapter 12 Navigating the Green Combustion Landscape: Optimizing Emissions and Performance in CI Engines Fuelled by Biogas and Nanoparticle-Doped Biodiesel
Chapter 13 A Differentiation Of Energy Storage Methods
Chapter 14 Application of IoT and Machine Learning to Improve Biogas Production Through Anaerobic Digestion
Chapter 15 Optimization of the Biogas Production Process: Role of Mathematical Modeling and Artificial Intelligence
Index
