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Computational Modeling Applications for Climate Crisis
Morgan Kaufmann Publishers In (Verlag)
978-0-443-21905-4 (ISBN)
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Dr. Utku Kose is an Associate Professor at Süleyman Demirel University, Turkey. He received his PhD from Selcuk University, Turkey, in the field of computer engineering. He has more than 100 publications to his credit, including Deep Learning for Medical Decision Support Systems, Springer; Artificial Intelligence Applications in Distance Education, IGI Global; Smart Applications with Advanced Machine Learning and Human-Centered Problem Design, Springer; Artificial Intelligence for Data-Driven Medical Diagnosis, DeGruyter; Computational Intelligence in Software Modeling, DeGruyter; Data Science for Covid-19, Volumes 1 and 2, Elsevier/Academic Press; and Deep Learning for Medical Applications with Unique Data, Elsevier/Academic Press, among others. Dr. Kose is a Series Editor of the Biomedical and Robotics Healthcare series from Taylor & Francis/CRC Press. His research interests include artificial intelligence, machine ethics, artificial intelligence safety, optimization, chaos theory, distance education, e-learning, computer education, and computer science. Dr. Deepak Gupta is an assistant professor at Maharaja Agrasen Institute of Technology, Delhi, India. He is an eminent academician, including roles as lecturer, researcher, consultant, community service, PhD, and post-doctorate supervision. Dr. Gupta focuses on rational and practical learning and has contributed important literature in the fields of Human-Computer Interaction, Intelligent Data Analysis, Nature-Inspired Computing, Machine Learning, and Soft Computing. Dr. Gupta has authored/edited a number of books, including Emerging Trends and Roles of Fog, Edge, and Pervasive Computing in Intelligent IoT-Driven Applications, Wiley; Advanced Machine Intelligence and Signal Processing, Springer; Deep Learning for Medical Applications with Unique Data, Elsevier/Academic Press; Explainable Edge AI: A Futuristic Computing Perspective, Springer; Applications of Big Data in Healthcare, Elsevier/Academic Press; and Data Science for Covid-19, Volumes 1 and 2, Elsevier/Academic Press; among others. Dr. Jose Antonio Marmolejo Saucedo is a Professor at Panamerican University, Mexico. His research is on large-scale optimization techniques, computational techniques, analytical methods for planning, operations, and control of electric energy and logistic systems, sustainable supply chain design, and digital twins in supply chains. He received his PhD in Operations Research (Hons) at National Autonomous University of Mexico. He is a member of the Network for Decision Support and Intelligent Optimization of Complex and Large Scale Systems, Mexican Society for Operations Research and System Dynamics Society. He is the author/editor of Computational Intelligence for Covid-19 and Future Pandemics, Springer; Modeling, Simulation, and Optimization, Springer; Data Analysis and Optimization for Engineering and Computing Problems, Springer; Artificial Intelligence for Renewable Energy and Climate Change, Wiley; Intelligent Computing and Optimization, Springer; and Innovative Computing Trends and Applications, Springer; among others.
1. Overview of Climate Change and Crisis
2. Computational Models for Tracking Parameters of the Climate Factors
3. Computational Modeling of Human Activities
4. Simulations for Climate Change
5. Visualizations for Better Interpretability of Climate Parameters
6. Data Fusion for Advanced Numerical Applications Against Climate Crisis
8. Decision Support Applications for Climate Crisis
9. Modeling of Technological Solutions for Climate Change
10. Modeling of Greenhouse Emissions for Predictive Purposes
11. Tracking of Climate Factors for Sustainability
12. Modeling of Earth Resources for Predictive Climate Change Management
13. Nation-based Outcomes for Numerical Analysis of Climate Change
14. Big Data and Computational Modeling Against Climate Crisis
15. Artificial Intelligence and Computational Modeling Against Climate Crisis
16. Modeling for Responsible Use of Technological Components
17. Optimization-Based Solutions to Deal with Climate Change
Erscheint lt. Verlag | 1.12.2024 |
---|---|
Reihe/Serie | Computational Modeling Applications for Existential Risks |
Verlagsort | San Francisco |
Sprache | englisch |
Maße | 191 x 235 mm |
Themenwelt | Mathematik / Informatik ► Informatik ► Theorie / Studium |
Informatik ► Weitere Themen ► Bioinformatik | |
Mathematik / Informatik ► Mathematik ► Angewandte Mathematik | |
Technik ► Maschinenbau | |
ISBN-10 | 0-443-21905-2 / 0443219052 |
ISBN-13 | 978-0-443-21905-4 / 9780443219054 |
Zustand | Neuware |
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