Optimization and Data Science in Industrial Engineering: Third International Conference, Odsie 2025, Istanbul, Turkey, November 20-22, 2025, Proceedin
暫譯: 工業工程中的優化與數據科學：第三屆國際會議 ODSIE 2025，土耳其伊斯坦堡，2025年11月20-22日，會議論文集

Name: Optimization and Data Science in Industrial Engineering: Third International Conference, Odsie 2025, Istanbul, Turkey, November 20-22, 2025, Proceedin
Price: 4047 TWD
Availability: OnlineOnly
Author: Molamohamadi, Zohreh, Babaee Tirkolaee, Erfan, Mirzazadeh, A.
ISBN: 3032170257

Molamohamadi, Zohreh, Babaee Tirkolaee, Erfan, Mirzazadeh, A.

Optimization and Data Science in Industrial Engineering: Third International Conference, Odsie 2025, Istanbul, Turkey, November 20-22, 2025, Proceedin

出版商: Springer
出版日期: 2026-02-03
售價: $4,260
貴賓價: 9.5 折 $4,047
語言: 英文
頁數: 255
裝訂: Quality Paper - also called trade paper
ISBN: 3032170257
ISBN-13: 9783032170255
相關分類: Data-mining、Machine Learning

海外代購書籍(需單獨結帳)

商品描述

This three-volume set CCIS 2854-2856 constitutes the refereed proceedings of the Third International Conference on Optimization and Data Science in Industrial Engineering, ODSIE 2025, held in Istanbul, Turkey, during November 20-22, 2025.

The 94 full papers and 10 short papers included in this book were carefully reviewed and selected from 198 submissions. They are organized into the following topical sections:

Part I: AI-Driven Innovations for Precision Medicine and Healthcare Optimization; Intelligent Optimization and Autonomous System Design through AI and Digital Technologies; AI and Policy-Based Cybersecurity Approaches for Urban Digital Infrastructure; Computational Intelligence and Data-Driven Strategies for Sustainable and Resilient Urban Systems; and Ethical and Legal Dimensions of Digital Governance in Modern Organizations.

Part II: Computational Governance and Ethical Intelligence in Global Corporate Systems; and Intelligent Optimization and Autonomous System Design through AI and Digital Technologies.

Part III: Data Analytics and AI for Cross-Sector Innovation and Global Development; and AI and Data-Driven Approaches for Sustainable Agriculture, Water Resources, and Food Systems.