Intelligent Technologies for Scientific Research and Engineering

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Bol Advanced Technologies for Science and Engineering - Vol. 4 is a comprehensive compilation of cutting-edge research at the intersection of artificial intelligence, data analytics, and advanced engineering applications. The book focuses on leveraging intelligent technologies to solve complex, real-world problems in today's data-driven landscape. Comprising thirty-seven peer-reviewed chapters, the volume blends theoretical foundations with practical implementations across diverse domains such as healthcare informatics, smart grids, energy forecasting, remote sensing, recommender systems, and climate modelling. It highlights innovative models, optimisation techniques, and scalable frameworks, supported by real-world case studies from industries including telecommunications, banking, e-commerce, and social media. Key Features -Extensive coverage of AI, machine learning, deep learning, and big data analytics. -46 peer-reviewed chapters combining theory with real-world applications. -Multidisciplinary topics, including healthcare, energy, climate science, and smart systems. -Focus on hybrid models, optimisation methods, and scalable frameworks. -Emphasis on contemporary challenges such as data privacy, sustainability, and intelligent automation.

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Advanced Technologies for Science and Engineering - Vol. 4 is a comprehensive compilation of cutting-edge research at the intersection of artificial intelligence, data analytics, and advanced engineering applications. The book focuses on leveraging intelligent technologies to solve complex, real-world problems in today's data-driven landscape. Comprising thirty-seven peer-reviewed chapters, the volume blends theoretical foundations with practical implementations across diverse domains such as healthcare informatics, smart grids, energy forecasting, remote sensing, recommender systems, and climate modelling. It highlights innovative models, optimisation techniques, and scalable frameworks, supported by real-world case studies from industries including telecommunications, banking, e-commerce, and social media. Key Features -Extensive coverage of AI, machine learning, deep learning, and big data analytics. -46 peer-reviewed chapters combining theory with real-world applications. -Multidisciplinary topics, including healthcare, energy, climate science, and smart systems. -Focus on hybrid models, optimisation methods, and scalable frameworks. -Emphasis on contemporary challenges such as data privacy, sustainability, and intelligent automation.

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Pagina's: 477, Paperback, Bentham Science Publishers


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  • 9798898815332
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