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Full Description
This book presents insights into how Intelligent Computing and Optimization techniques can be used to attain the goals of Sustainable Development. It provides a comprehensive overview of the latest breakthroughs and recent developments in sustainable, intelligent computing technologies, applications, and optimization techniques across various industries, including business process management, manufacturing, financial sector, agriculture, financial sector, supply chain management, and healthcare. It focuses on computational intelligent techniques and optimization techniques to provide sustainable solutions to many problems.
Features:
Provides insights into the theory, implementation, and application of computational intelligence techniques in many industries
Includes industry practitioner perspectives and case studies for a better understanding of sustainable solutions
Highlights the role of intelligent computing and optimization as key technologies in decision-making processes and in providing cutting-edge solutions to real-world problems
Addresses the challenges and limitations of computational approaches in sustainability, such as data availability, model uncertainty, and computational complexity, while also discusses emerging opportunities and future directions in the field
This book will be useful for professionals and scholars looking for up-to-date research on cutting-edge perspectives in the field of computational intelligent and optimization techniques in the areas of agriculture, industry, financial sector, business automation, renewable energy, optimization, and smart cities.
The Open Access version of this book, available at http://www.taylorfrancis.com, has
been made available under a Creative Commons [Attribution-Non Commercial-No
Derivatives (CC BY-NC-ND)] 4.0 license.
Contents
1. A Journey to Computational Intelligence in Sustainable Development. 2. Business Combining Artificial Intelligence Concentrating on Sustainable Development Goals: A Win-Win situation 3. Deep Neural Networks (DNN) for Sustainable Development for Smart Cities 4. Digital Task Optimization with Resource Allocation in Business Process Management Using Machine Learning Model 5. Design of an Efficient Multi Model Deep Learning Framework for Assessing Mental Workload using Eye Tracking & Physiological Parameters 6. Deep Learning in Smart Manufacturing: Advancements, Applications, and Challenges 7. Fuzzy Optimization Techniques in Agricultural Field using Supply Chain Management 8. Computational Techniques for Banking and Financial Sectors 9. Smart Computing for Green Sustainability 10. Sustainable Manufacturing for Industry 4.0: Navigating the Path to Environmental Responsibility 11. Blockchain Technology for Agriculture Supply Chain Management 12. Computational Intelligence for Biodiversity Conservation 13. Sailing the Waves of Sustainable Entrepreneurship: Unveiling the Moderator Role of Technological Adoption in SMEs Innovation 14. Robotic Process Automation: The Tangible and Human Shift in Business Process Efficiency.
