Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning - Lefteri H Tsoukalas
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Présentation Fuzzy Logic: Applications In Artificial Intelligence, Big Data, And Machine Learning de Lefteri H Tsoukalas Format...
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Résumé : Fuzzy logic principles, practices, and real-world applications This hands-on guide offers clear explanations of fuzzy logic along with practical applications and real-world examples. Written by an award-winning engineer, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and motivation in students and professionals alike. Inside, you will discover how to apply fuzzy logic in the context of pervasive digitization and big data across emerging technologies which require a very different man-machine relationship than the ones previously used in engineering, science, economics, and social sciences. Applications covered include intelligent energy systems with demand response, smart homes, electrification of transportation, supply chain efficiencies, smart cities, e-commerce, education, healthcare, and decarbonization.
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Biographie:
Lefteri H. Tsoukalas is a professor of engineering and founding director of the AI Systems Lab at Purdue University. He has three decades of experience in intelligent systems with over 300 research publications and is the author of Fuzzy and Neural Approaches in Engineering. Dr. Tsoukalas is a fellow of the American Nuclear Society and the 2009 recipient of the Humboldt Prize. ...
Sommaire: Fuzzy logic principles, practices, and real-world applications This hands-on guide offers clear explanations of fuzzy logic along with practical applications and real-world examples. Written by an award-winning engineer, Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning is aimed at improving competence and motivation in students and professionals alike. Inside, you will discover how to apply fuzzy logic in the context of pervasive digitization and big data across emerging technologies which require a very different man-machine relationship than the ones previously used in engineering, science, economics, and social sciences. Applications covered include intelligent energy systems with demand response, smart homes, electrification of transportation, supply chain efficiencies, smart cities, e-commerce, education, healthcare, and decarbonization.
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