Fuzzy logic principles, practices, and real-world applicationsThis 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.Serves as a classroom guide and as an on-the-job resourceAncillaries include a sample syllabus, test sets with answer keys, and additional self-study resources for studentsWritten by an expert in the field and experienced author.

N� de ref. del art�culo LU-9781264675913

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Detalles bibliogr�ficos

T�tulo: Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning
Editor: McGraw-Hill Education, US
Fecha de publicaci�n: 2023
Idioma: Ingl�s
ISBN 10: 1264675917
ISBN 13: 9781264675913
Encuadernaci�n: Paperback
Estado: New

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Sinopsis

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.

Serves as a classroom guide and as an on-the-job resource
Ancillaries include a sample syllabus, test sets with answer keys, and additional self-study resources for students
Written by an expert in the field and experienced author

Acerca del autor

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.

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