1st Edition
Machine Learning and Probabilistic Graphical Models for Decision Support Systems
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
Kim Phuc Tran
2. Decision Support Systems for Healthcare based on Probabilistic Graphical Models: A Survey and Perspective
Ali Raza, Kim Phuc Tran, Ludovic Koehl, and Shujun Li
3. Decision Support Systems for Anomaly Detection with the Applications in Smart Manufacturing: A Survey and Perspective
Quoc-Thông Nguyen, Tung Nhi Tran, Cédric Heuchenne and Kim Phuc Tran
4. Decision Support System for Complex Systems Risk Assessment with Bayesian Networks
Ayeley Tchangani
5. Decision Support System using LSTM with bayesian optimization for Predictive Maintenance: Remaining Useful Life Prediction
Huu Du Nguyen and Kim Phuc Tran
6. Decision Support Systems for Textile Manufacturing Process with Machine Learning
Zaohao Lu, Zhenglei He, Kim Phuc Tran, Sebastien Thomassey, Xianyi Zeng, and Mengna Hong
7. Anomaly Detection Enables Cybersecurity with Machine Learning Techniques
Truong Thu Huong, Nguyen Minh Dan, Le Anh Quang, Nguyen Xuan Hoang, Le Thanh Cong, Kieu-Ha Phung, and Kim Phuc Tran
8. Machine Learning for Compositional Data Analysis in Support of the Decision Making Process
Thi Thuy Van Nguyen, Cédric Heuchenne and Kim Phuc Tran
9. Decision Support System with Genetic Algorithm for Economic Statistical Design of Nonparametric Control Chart
Alejandro Marcos Alvarez, Cédric Heuchenne, Phuong Hanh Tran, and Alireza Faraz
10. Jamming Detection in Electromagnetic Communication with Machine Learning: A Survey and Perspective
Jonathan Villain, Virginie Deniau, and Christophe Gransart
11. Intellectual Support with Machine Learning for Decision-making in Garment Manufacturing Industry: A Review
Yanni Xu and Xiaofen Ji
12. Enabling Smart Supply Chain Management with Artificial Intelligence
Thi Hien Nguyen, Huu Du Nguyen, Kim Duc Tran, Dinh Duy Kha Nguyen, and Kim Phuc Tran
Biography
Kim Phuc Tran is an Associate Professor of Artificial Intelligence and Data Science at ENSAIT & GEMTEX,
University of Lille, France, and a Senior Scientific Advisor at Dong A University, Vietnam. He obtained a Ph.D. in
Automation and Applied Informatics at the University of Nantes, and an HDR (Dr. Habil.) in Computer Science and
Automation at the University of Lille, France. His research focuses on Artificial Intelligence and applications. He has
published more than 60 papers in SCIE peer-reviewed international journals and proceedings of international conferences. He edited 3 books with Springer Nature and CRC Press, Taylor & Francis Group.
