Computational Intelligence for Climate Change

This book stands out in the field due to its interdisciplinary approach, integrating cutting-edge computational methods with environmental sciences to offer practical solutions for sustainable development. One of the most important worldwide issues of our day is climate change, which calls for creative, data-driven, and scalable solutions. A thorough examination of how computational intelligence (CI) methods can be applied to different facets of climate change, from assessing its effects to developing mitigation and adaptation plans, can be found in the book. The chapters explain how these tools can be harnessed to tackle the complexities of climate change. The book contextualizes climate change as a data-rich problem, highlighting the challenges posed by its vast, heterogeneous, and dynamic datasets. The book also discusses about climate data analytics, which discusses the role of CI in managing and analyzing large-scale climate data collected from satellites, weather stations, and IoT devices. This book presents techniques for preprocessing, cleaning, and normalizing climate data to enhance its usability. This book details the use of computational intelligence for creating accurate climate models. This book explores techniques for predicting long-term trends, such as global warming and sea level rise, and short-term events like hurricanes and heatwaves. Case studies demonstrate how machine learning algorithms, such as random forests and support vector machines, have been used to refine predictive models. It presents vulnerability analysis frameworks that use CI to assess the susceptibility of regions, ecosystems, and communities to climate risks. The book discusses real-world applications, such as identifying drought-prone areas using neural networks or assessing flood risks using fuzzy logic systems. The book delves into the integration of CI with emerging technologies such as blockchain, quantum computing, and the Internet of Things (IoT) for more robust climate solutions.

List of contents

Foundations of Computational Intelligence for Climate Applications.- Big Data Analytics in Climate Science.- Machine Learning Models for Climate Prediction.- Deep Learning Techniques in Climate Forecasting.- Climate Change Impact Analysis Using Fuzzy Systems.- Evolutionary Algorithms for Optimizing Renewable Energy Systems.- Climate Vulnerability Assessment with Neural Networks.- Intelligent Systems for Carbon Emission Monitoring.- CI Applications in Climate-Resilient Agriculture.- Smart Urban Planning: A CI Perspective.- Blockchain-Enabled Transparency in Climate Solutions.- IoT-Driven Data Collection and CI Integration.- Real-Time Weather Anomaly Detection Using CI.- Hybrid Models for Climate Adaptation Strategies.- Geoengineering and CI: Innovations for Climate Mitigation.- Ethical Challenges in Computational Climate Intelligence.- Quantum Computing for Advanced Climate Modeling.- Interdisciplinary Approaches to Climate Intelligence.- Case Studies: Successful CI Applications in Climate Action.- The Future of Computational Intelligence in Combating Climate Change.

About the author

Dr. A. Jose Anand is Professor at the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, India. He has one year of industrial experience and over twenty-five years of teaching experience. He has presented several papers in prominent conferences and has published several papers in reputed journal and also published books in professional and engineering subjects. He is Member of Institution of Engineers, Computer Society of India, Institution of Engineering and Technology, Indian Society for Technical Education, etc. His current research interests include wireless sensor networks, embedded systems, IoT, machine learning, image processing, etc.
Dr. Saravanan Krishnan is Associate Professor, Department of Computer Science and Engineering in College of Engineering, Guindy, Anna University, Chennai, India. He is also Deputy Director for Centre for University-Industry Collaboration (CUIC), Anna University, Chennai. He has a masters in software engineering and Ph.D. in computer science and engineering. His research interests include cloud computing, blockchain, software engineering, IoT, smart cities. He has published papers in a number of conferences and reputed journals. He has also written 21 book chapters and edited 15 books with major publishers. He has been Consultant to municipal corporations and smart city schemes. He is Active Researcher and Academician and is Reviewer for many reputed journals. He is Fellow of Institution of Engineers and Senior Member of Association of Computing Machinery, Indian Society for Technical Education, etc.
Professor Walter Leal is Distinguished "Euro-Professor", holding professorial posts at Universities in Germany (Chair of Climate Change Management at the Hamburg University of Applied Sciences), United Kingdom (Manchester Metropolitan University), Sweden (University of Uppsala) and Poland (Merito University). He has two main research interests. The first is in the field of sustainable development, where he holds a world record of publications. The second is climate change, to which he has been providing a key contribution to the literature, also including aspects of climate change and health. His field experience in over 70 countries involves missions undertaken on behalf of various international organizations (e.g., European Union, World Bank, OECD, UNESCO, UNEP) and attendance to specialized events in North America, Latin America/Caribbean, Europe, Africa, Asia and Pacific Region, and the Middle East. Moreover, he was awarded the “Golden Page Award” (April 2003) in London for his editorial work.

Summary

This book stands out in the field due to its interdisciplinary approach, integrating cutting-edge computational methods with environmental sciences to offer practical solutions for sustainable development. One of the most important worldwide issues of our day is climate change, which calls for creative, data-driven, and scalable solutions. A thorough examination of how computational intelligence (CI) methods can be applied to different facets of climate change, from assessing its effects to developing mitigation and adaptation plans, can be found in the book. The chapters explain how these tools can be harnessed to tackle the complexities of climate change. The book contextualizes climate change as a data-rich problem, highlighting the challenges posed by its vast, heterogeneous, and dynamic datasets. The book also discusses about climate data analytics, which discusses the role of CI in managing and analyzing large-scale climate data collected from satellites, weather stations, and IoT devices. This book presents techniques for preprocessing, cleaning, and normalizing climate data to enhance its usability. This book details the use of computational intelligence for creating accurate climate models. This book explores techniques for predicting long-term trends, such as global warming and sea level rise, and short-term events like hurricanes and heatwaves. Case studies demonstrate how machine learning algorithms, such as random forests and support vector machines, have been used to refine predictive models. It presents vulnerability analysis frameworks that use CI to assess the susceptibility of regions, ecosystems, and communities to climate risks. The book discusses real-world applications, such as identifying drought-prone areas using neural networks or assessing flood risks using fuzzy logic systems. The book delves into the integration of CI with emerging technologies such as blockchain, quantum computing, and the Internet of Things (IoT) for more robust climate solutions.

Product details

• Assisted by: A. Jose Anand (Editor), Saravanan Krishnan (Editor), Walter Leal (Editor)
• Publisher: Springer International Publishing
• Languages: English
• Product format: Hardback
• Release: 21.03.2026
• EAN: 9783032168030
• ISBN: 978-3-032-16803-0
• Illustrations: Approx. 425 p. 70 illus., 10 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
• Series: Climate Change Management
• Subjects: Natural sciences, medicine, IT, technology > Geosciences > Miscellaneous; Sustainability, Künstliche Intelligenz, machine learning, Maschinelles Lernen, Climate Change, Global Warming, Internet of things, big data analytics, Agriculture, Quantum Computing, Computational Intelligence, Climate Sciences, Climate Mitigation, Smart Urban Planning