nach der Bestellung gedruckt Neuware - Printed after ordering - In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change. Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials.

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Bibliographic Details

Title: Using Traditional Design Methods to Enhance AI-Driven Decision Making
Publisher: IGI Global
Publication Date: 2024
Language: English
ISBN 13: 9798369306390
Binding: Buch
Condition: Neu
Dimensions: 286 millimeters width by 221 millimeters height by 33 millimeters depth
Weight: 1592 grams

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"Through its thought-provoking chapters, it aims to deepen the understanding of AI-Driven decision-making in higher education leadership and equip readers with the necessary knowledge and resources to embrace and leverage the potential of AI in decision-making processes"--

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