Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning

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COMMUNICATION NETWORKS AND SERVICE MANAGEMENT IN THE ERA OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Discover the impact that new technologies are having on communication systems with this up-to-date and one-stop resource Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning delivers a comprehensive overview of the impact of artificial intelligence (AI) and machine learning (ML) on service and network management. Beginning with a fulsome description of ML and AI, the book moves on to discuss management models, architectures, and frameworks. The authors also explore how AI and ML can be used in service management functions like the generation of workload profiles, service provisioning, and more. The book includes a handpicked selection of applications and case studies, as well as a treatment of emerging technologies the authors predict could have a significant impact on network and service management in the future. Statistical analysis and data mining are also discussed, particularly with respect to how they allow for an improvement of the management and security of IT systems and networks. Readers will also enjoy topics like: A thorough introduction to network and service management, machine learning, and artificial intelligence An exploration of artificial intelligence and machine learning for management models, including autonomic management, policy-based management, intent based ­management, and network virtualization-based management Discussions of AI and ML for architectures and frameworks, including cloud ­systems, software defined networks, 5G and 6G networks, and Edge/Fog networks An examination of AI and ML for service management, including the automatic ­generation of workload profiles using unsupervised learning Perfect for information and communications technology educators, Communication Networks and Service Management in the Era of Artificial Intelligence and Machine Learning will also earn a place in the libraries of engineers and professionals who seek a structured reference on how the emergence of artificial intelligence and machine learning techniques is affecting service and network management.

Operations Management in the Supply Chain: Decisions and Cases (8版)

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Operations Management in the Supply Chain: Decisions and Cases 作 / 譯 者 ： Roger G. Schroeder,Susan Meyer Goldstein I S B N - 13 ： 9781260571431 I S B N - 10 ： 1260571432 類 別： 生產與作業管理 版 次： 8 版 年 份： 2021 規 格： 519 頁 出 版 商： McGraw Hill Education 內容簡介 　　Appropriate for both undergraduates and MBA students, Operations Management in the Supply Chain: Decisions and Cases, 8e is a guide to operations that takes a unique approach to decision making with a strong emphasis on case materials to put concepts into practice. It provides a balanced treatment of both service and manufacturing firms in a fully updated 4 color revision with modern real-world topics, more Connect content and case solutions. This is the first book to include cross functional decision making for non-majors. In addition, current knowledge is included on global operations, supply chain management, competency-based strategy, Six Sigma, lean systems, artificial intelligence, analytics, sustainability, supply chain risk, and digital technology content like 3D printing and blockchain. Enhanced Connect content includes, SmartBook 2.0, OMintheNews, Practice Operations, and Interactive Data Problems designed to help students visualize key concepts. 目錄 PART I: INTRODUCTION Ch 1 Introduction to Operations Ch 2 Operations and Supply Chain Strategy Ch 3 Product Design PART II: PROCESS DESIGN Ch 4 Process Selection Ch 5 Service Process Design Ch 6 Process-Flow Analysis Ch 7 Lean Thinking and Lean Systems PART III: QUALITY Ch 8 Managing Quality Ch 9 Quality Control and Improvement PART IV: CAPACITY AND SCHEDULING Ch10 Forecasting Supplement: Advanced Methods Ch11 Capacity Planning Ch12 Scheduling Operations Ch13 Project Planning and Scheduling PART V: INVENTORY Ch14 Independent Demand Inventory Supplement: Advanced Models Ch15 Materials Requirements Planning and ERP PART VI: SUPPLY CHAIN DECISIONS Ch16 Supply Chain Management Ch17 Sourcing Ch18 Global Logistics PART VII: CASE STUDIES