Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning

Lefteri Tsoukalas

ISBN 10: 1264675917 / ISBN 13: 9781264675913

Edité par McGraw-Hill Education, US, 2023

A propos de cet article

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 réf. du vendeur LU-9781264675913

Détails bibliographiques

• Titre: Fuzzy Logic: Applications in Artificial Intelligence, Big Data, and Machine Learning
• Éditeur: McGraw-Hill Education, US
• Date de parution: 2023
• Langue: anglais
• ISBN à 10 chiffres: 1264675917
• ISBN à 13 chiffres: 9781264675913
• Reliure: Paperback
• État de l'article: New

A propos de ce titre

Synopsis

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

À propos de l?auteur

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.