Computational Optimization Techniques for Artificial Intelligence Enabled Environments
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Beschreibung
This book introduces cutting-edge computational optimization techniques designed especially for AI enabled systems. These techniques inculcate advanced algorithms with real world applications to enhance efficiency and accuracy. Its focus on the hybrid and ensemble models makes it stand out, presenting novel and creative solutions for the complex problems. Through case studies and real-world applications the book not only highlights the theoretical aspects of the optimization techniques but also provides a link between theory and practice. With the help of clear explanations and practical examples the book empowers the readers to delve into the complex problems and providing optimized solutions leading to enhancing the performance of AI enabled systems.
The book explores the advanced computational optimization techniques covering wide range of topics like nature-inspired algorithms, metaheuristics and hybrid optimization methods. This book caters the need of AI researchers, data scientists and machine learning engineers who aim to optimize their models and algorithms. It will be a valuable resource for the academicians and students studying AI and its related subfield. Professionals in the field of finance, healthcare, agriculture, education where AI applications are prevalent, will benefit from the practical insights provided. Overall, it caters to anyone interested in enhancing AI systems through sophisticated optimization strategies.
This book introduces cutting-edge computational optimization techniques designed especially for AI enabled systems. These techniques inculcate advanced algorithms with real world applications to enhance efficiency and accuracy. Its focus on the hybrid and ensemble models makes it stand out, presenting novel and creative solutions for the complex problems. Through case studies and real-world applications the book not only highlights the theoretical aspects of the optimization techniques but also provides a link between theory and practice. With the help of clear explanations and practical examples the book empowers the readers to delve into the complex problems and providing optimized solutions leading to enhancing the performance of AI enabled systems.
The book explores the advanced computational optimization techniques covering wide range of topics like nature-inspired algorithms, metaheuristics and hybrid optimization methods. This book caters the need of AI researchers, data scientists and machine learning engineers who aim to optimize their models and algorithms. It will be a valuable resource for the academicians and students studying AI and its related subfield. Professionals in the field of finance, healthcare, agriculture, education where AI applications are prevalent, will benefit from the practical insights provided. Overall, it caters to anyone interested in enhancing AI systems through sophisticated optimization strategies.
Provides case studies and practical examples of optimization in AI-enabled environments, illustrating industry impacts Focuses on latest advancements in computational optimization such as hybrid algorithms Demonstrates how metaheuristics can advance SDGs like climate action, clean energy, and sustainable cities
Autor*in
Shilpa Srivastava
Themen in »Computational Optimization Techniques for Artificial Intelligence Enabled Environments«
Nature Inspired Optimization Heuristic Optimization Numerical Optimization Deep Learning Optimization Ensemble Optimization Techniques Smart Cities