Computational Intelligence Methods For Green Technology And Sustainable Development
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| Author | : Yo-Ping Huang |
| Publisher | : Springer Nature |
| Total Pages | : 685 |
| Release | : 2022-12-14 |
| Genre | : Technology & Engineering |
| ISBN | : 3031196945 |
This book provides readers with peer-reviewed research papers presented at the 6th International Conference on Green Technology and Sustainable Development (GTSD) held in Nha Trang City, Vietnam, from July 29 to 30, 2022. The book is original work of researchers from academia and industry focusing on the theme “Green technology and sustainable development in Industrial Revolution 4.0” not only to raise awareness of the vital importance of sustainability in education, technology, and economic development, but also to highlight the essential roles of technology innovation for the green future. The book presents a wide range of research aspects including energy engineering, electric power systems, renewable energy systems, automatic control engineering, robotics, vehicle engineering, material engineering, construction engineering, mechanical engineering, vibrations, computational analysis, numerical investigation, system failure, technological solutions in health care, and so on. Through thorough research basing on both experimental and numerical methods, the authors feature either solutions for existing problems or optimization and improvement for performance of existing methods. The collected research results could be useful alternatives and implications for industry experts, research institutions, universities, and all others who share a common interest in the future global sustainable development.
| Author | : Yo-Ping Huang |
| Publisher | : Springer Nature |
| Total Pages | : 655 |
| Release | : 2020-10-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3030623246 |
This book is a selected collection of 54 peer-reviewed original scientific research papers of the 5th International Conference on Green Technology and Sustainable Development (GTSD2020) organised in Vietnam in 2020. It highlights the importance of sustainability as well as promotes up-to-date innovation and research for green development in technologies, economics and education among countries. The conference provides an international platform for researchers, practitioners, policymakers and entrepreneurs to present their advances, knowledge and experience on various interdisciplinary topics related to the theme of “Green technology and sustainable development in industrial revolution 4.0”. The book is a valuable resource for researchers, analysts, engineers, practitioners and policymakers who are interested in the latest findings in artificial intelligence, cyber systems, robotics, green energy and power systems, mechanical and computational mechanic models and advanced civil engineering. This book has 05 sessions consisting of both theoretical and practical aspects, and numerical and experimental analyses in various engineering disciplines.
| Author | : Ting Yu |
| Publisher | : CRC Press |
| Total Pages | : 443 |
| Release | : 2016-04-19 |
| Genre | : Business & Economics |
| ISBN | : 1439895953 |
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
| Author | : Aboul Ella Hassanien |
| Publisher | : Springer Nature |
| Total Pages | : 310 |
| Release | : 2020-08-31 |
| Genre | : Technology & Engineering |
| ISBN | : 3030519201 |
This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.
| Author | : Krishna Kumar |
| Publisher | : Academic Press |
| Total Pages | : 418 |
| Release | : 2022-03-18 |
| Genre | : Technology & Engineering |
| ISBN | : 0323914284 |
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
| Author | : José Luis Verdegay |
| Publisher | : Springer Nature |
| Total Pages | : 301 |
| Release | : 2022-04-15 |
| Genre | : Technology & Engineering |
| ISBN | : 3030973441 |
This book presents computational intelligence methodologies and its applications to sustainable development goals. Along 18 chapters prepared by reputed scientists around the world, this book explores and focuses on the impacts produced by the application of artificial intelligence and mainly of computational intelligence, in sustainable development goals and on analysing how particularly computational intelligence can influence the ability to comply in a timely manner with all the sustainable development goals. Specialists from STEM areas will find in this book an attractive showcase of instances and research lines to be explored.
| Author | : Yo-Ping Huang |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2021 |
| Genre | : |
| ISBN | : 9783030623258 |
This book is a selected collection of 54 peer-reviewed original scientific research papers of the 5th International Conference on Green Technology and Sustainable Development (GTSD2020) organised in Vietnam in 2020. It highlights the importance of sustainability as well as promotes up-to-date innovation and research for green development in technologies, economics and education among countries. The conference provides an international platform for researchers, practitioners, policymakers and entrepreneurs to present their advances, knowledge and experience on various interdisciplinary topics related to the theme of "Green technology and sustainable development in industrial revolution 4.0". The book is a valuable resource for researchers, analysts, engineers, practitioners and policymakers who are interested in the latest findings in artificial intelligence, cyber systems, robotics, green energy and power systems, mechanical and computational mechanic models and advanced civil engineering. This book has 05 sessions consisting of both theoretical and practical aspects, and numerical and experimental analyses in various engineering disciplines.
| Author | : Sanjoy Kumar Paul |
| Publisher | : Elsevier |
| Total Pages | : 470 |
| Release | : 2024-05-24 |
| Genre | : Computers |
| ISBN | : 0443184658 |
Sustainable supply chain management involves integrating environmentally and financially viable practices into the complete supply chain lifecycle, from product design and development to material selection and sourcing, manufacturing, packaging, transportation, and distribution. A sustainable supply chain ensures balance between economic, social, and environmental performances – such as better assurance of human rights, ethical work practices, carbon footprint reduction, waste management, and resource efficiency. Computational Intelligence Techniques for Sustainable Supply Chain Management presents state-of-the-art computational intelligence techniques and applications for supply chain sustainability issues and logistic problems, filling the gap between general textbooks on sustainable supply chain management and more specialized literature dealing with methods for computational intelligence. This book focuses on addressing problems in advanced topics in the sustainable supply chain, and will appeal to practitioners, managers, researchers, academicians, students, and professionals interested in sustainable logistics, sustainable procurement, sustainable manufacturing, sustainable inventory and production management, sustainable scheduling, sustainable transportation, and sustainable network design. - Serves as a reference on computational intelligence–enabled sustainable supply chains for graduate students in computer/data science, industrial engineering, industrial ecology, and business - Explores key topics in sustainable supply chain informatics, that is, heuristics, metaheuristics, robotics, simulation, machine learning, big data analytics and artificial intelligence - Provides a foundation for industry leaders and professionals to understand recent and cutting-edge methodologies and technologies in the domain of sustainable supply chain powered by computational intelligence techniques
| Author | : Lorenz M. Hilty |
| Publisher | : Springer |
| Total Pages | : 465 |
| Release | : 2014-08-06 |
| Genre | : Technology & Engineering |
| ISBN | : 3319092286 |
ICT Innovations for Sustainability is an investigation of how information and communication technology can contribute to sustainable development. It presents clear definitions of sustainability, suggesting conceptual frameworks for the positive and negative effects of ICT on sustainable development. It reviews methods of assessing the direct and indirect impact of ICT systems on energy and materials demand, and examines the results of such assessments. In addition, it investigates ICT-based approaches to supporting sustainable patterns of production and consumption, analyzing them at various levels of abstraction – from end-user devices, Internet infrastructure, user behavior, and social practices to macro-economic indicators. Combining approaches from Computer Science, Information Systems, Human-Computer Interaction, Economics, and Environmental Sciences, the book presents a new, holistic perspective on ICT for Sustainability (ICT4S). It is an indispensable resource for anyone working in the area of ICT for Energy Efficiency, Life Cycle Assessment of ICT, Green IT, Green Information Systems, Environmental Informatics, Energy Informatics, Sustainable HCI, or Computational Sustainability.
| Author | : Jennifer Dunn |
| Publisher | : Elsevier |
| Total Pages | : 312 |
| Release | : 2021-05-11 |
| Genre | : Science |
| ISBN | : 0128179775 |
Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses
