意思決定支援システムのための機械学習・確率論的図表モデル Machine Learning and Probabilistic Graphical Models for Decision Support Systems

意思決定支援システムのための機械学習・確率論的図表モデル<br>Machine Learning and Probabilistic Graphical Models for Decision Support Systems

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意思決定支援システムのための機械学習・確率論的図表モデル
Machine Learning and Probabilistic Graphical Models for Decision Support Systems

Tran, Kim Phuc (EDT)

ウェブストア価格 ¥43,464（本体¥39,513）
CRC Press（2022/10発売）
外貨定価 US$ 210.00
ポイント 395pt

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製本 Hardcover:ハードカバー版／ページ数 318 p.
言語 ENG
商品コード 9781032039480
DDC分類 006.31

Full Description

This book presents recent advancements in research, a review of new methods and techniques, and applications in decision support systems (DSS) with Machine Learning and Probabilistic Graphical Models, which are very effective techniques in gaining knowledge from Big Data and in interpreting decisions. It explores Bayesian network learning, Control Chart, Reinforcement Learning for multicriteria DSS, Anomaly Detection in Smart Manufacturing with Federated Learning, DSS in healthcare, DSS for supply chain management, etc. Researchers and practitioners alike will benefit from this book to enhance the understanding of machine learning, Probabilistic Graphical Models, and their uses in DSS in the context of decision making with uncertainty. The real-world case studies in various fields with guidance and recommendations for the practical applications of these studies are introduced in each chapter.

1. Introduction to Machine Learning and Probabilistic Graphical Models for Decision Support Systems 2. Decision Support Systems for Healthcare based on Probabilistic Graphical Models: A Survey and Perspective 3. Decision Support Systems for Anomaly Detection with the Applications in Smart Manufacturing: A Survey and Perspective 4. Decision Support System for Complex Systems Risk Assessment with Bayesian Networks 5. Decision Support System using LSTM with Bayesian Optimization for Predictive Maintenance: Remaining Useful Life Prediction 6. Decision Support Systems for Textile Manufacturing Process with Machine Learning 7. Anomaly Detection Enables Cybersecurity with Machine Learning Techniques 8. Machine Learning for Compositional Data Analysis in Support of the Decision Making Process 9. Decision Support System with Genetic Algorithm for Economic Statistical Design of Nonparametric Control Chart 10. Jamming Detection in Electromagnetic Communication with Machine Learning: A Survey and Perspective 11. Intellectual Support with Machine Learning for Decision-making in Garment Manufacturing Industry: A Review 12. Enabling Smart Supply Chain Management with Artificial Intelligence