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Beschreibung
This book delivers a practical, forward-looking guide to cutting-edge developments at the intersection of information science, computing, and technology, equipping readers to bridge theoretical advancements with real-world application. By prioritizing actionable insights over abstract theory, it addresses the gap between rapid tech evolution and the need for accessible, applicable knowledge for professionals and learners alike.

Rather than organizing content by traditional subdisciplines, this book adopts an interdisciplinary, problem-centric approach This novelty ensures readers grasp how technologies interact to solve complex challenges, a perspective often missing in more siloed texts.

Intended for a broad audience, it serves as a go-to resource for tech professionals seeking to update their skills, upper-level undergraduate/graduate students in related fields, and researchers needing a concise overview of cross-domain progress.
This book delivers a practical, forward-looking guide to cutting-edge developments at the intersection of information science, computing, and technology, equipping readers to bridge theoretical advancements with real-world application. By prioritizing actionable insights over abstract theory, it addresses the gap between rapid tech evolution and the need for accessible, applicable knowledge for professionals and learners alike.

Rather than organizing content by traditional subdisciplines, this book adopts an interdisciplinary, problem-centric approach This novelty ensures readers grasp how technologies interact to solve complex challenges, a perspective often missing in more siloed texts.

Intended for a broad audience, it serves as a go-to resource for tech professionals seeking to update their skills, upper-level undergraduate/graduate students in related fields, and researchers needing a concise overview of cross-domain progress.
Inhaltsverzeichnis

Prediction and Analysis of the Trend of Economic Management Strategy of Tourism Industry by Neural Network Model.- Research on the Application of Big Data-Driven Multi-Agent Reinforcement Learning in Autonomous Driving Traffic Control.- Low-Carbon Green Indicator System for Transportation Logistics and Energy Efficiency Optimization Methods.

Details
Erscheinungsjahr: 2026
Fachbereich: Technik allgemein
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xviii
530 S.
37 s/w Illustr.
179 farbige Illustr.
530 p. 216 illus.
179 illus. in color.
ISBN-13: 9783032119568
ISBN-10: 3032119561
Sprache: Englisch
Herstellernummer: 89570992
Einband: Kartoniert / Broschiert
Redaktion: Pedrycz, Witold
Wang, John
Li, Jianqi
Herausgeber: Witold Pedrycz/John Wang/Jianqi Li
Hersteller: Springer
Springer International Publishing AG
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 30 mm
Von/Mit: Witold Pedrycz (u. a.)
Erscheinungsdatum: 15.01.2026
Gewicht: 0,82 kg
Artikel-ID: 134465370