Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications

Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. This book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources. Computational intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. Data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable. Presents computational intelligence-based data analysis for sustainable computing applications such as pattern recognition, biomedical imaging, sustainable cities, sustainable transport, sustainable agriculture, and sustainable financial management.Develops research in sustainable computing and optimization, combining methods from engineering, mathematics, and computer science to optimize environmental resources.Includes three foundational chapters dedicated to providing an overview of computational intelligence and optimization techniques and how they can be applied to sustainable computing. INDICE: 1. Journey of Computational intelligence in sustainable computing and optimization techniques: An introduction2. Designing computational intelligence techniques based smart framework for Sustainable Computing3. Multiple Parameter Optimization Methods Based on Computational Intelligence Techniques in Context of Sustainable Computing4. Sustainable Computing Based Deep Learning Framework for fault detection in Industry 4.0 heterogeneous data environments5. IoT based vulnerability assessment for sustainable computing: threats, current solutions, and open challenges6. Amalgamation of optimization techniques in big data analytics through granular computing: A roadmap to smart industry framework7. Computational intelligence for data analysis in pattern recognition and Biomedical imaging8. A block chain and artificial intelligence enabled smart IoT framework for the development of sustainable city9. Computational intelligence based heuristic approach for maximizing energy efficiency in Sustainable Transportation and Mobility10. Computational Intelligence for sustainable computing in Health Care informatics11. Designing a classification model based on Computational intelligence for effective Stock market analysis and financial management12. Artificial Intelligence based Computational intelligence solution for robotics automation13. Developing Green Computing Awareness based on optimization techniques for Environmental Sustainability14. Assimilation of Soft Computing and Optimization Techniques for Sustainable Agriculture evolution strategy15. Bio-inspired meta-heuristic algorithm for solving engineering optimization problems based on computational intelligence16. Cryptography and Cryptanalysis Through Computational Intelligence17. Private Blockchain-based Encryption Framework Using Computational Intelligence Approach

• ISBN: 978-0-443-23724-9
• Editorial: Morgan Kaufmann
• Encuadernacion: Rústica
• Páginas: 250
• Fecha Publicación: 01/10/2024
• Nº Volúmenes: 1
• Idioma: Inglés