Data Mining and Knowledge Discovery for Process Monitoring and Control
(Sprache: Englisch)
Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer...
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Klappentext zu „Data Mining and Knowledge Discovery for Process Monitoring and Control “
Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.
Modern computer-based control systems are able to collect a large amount of information, display it to operators and store it in databases but the interpretation of the data and the subsequent decision making relies mainly on operators with little computer support. This book introduces developments in automatic analysis and interpretation of process-operational data both in real-time and over the operational history, and describes new concepts and methodologies for developing intelligent, state space-based systems for process monitoring, control and diagnosis. The book brings together new methods and algorithms from process monitoring and control, data mining and knowledge discovery, artificial intelligence, pattern recognition, and causal relationship discovery, as well as signal processing. It also provides a framework for integrating plant operators and supervisors into the design of process monitoring and control systems.
Inhaltsverzeichnis zu „Data Mining and Knowledge Discovery for Process Monitoring and Control “
- Introduction- Data Mining and Knowledge Discovery - an Overview
- Data Pre-processing for Feature Extraction, Dimension Reduction and Concept Formation
- Multivariate Statistical Analysis for Data Analysis and Statistical Control
- Supervised Learning for Operational Support
- Unsupervised Learning for Operational State Identification
- Inductive Learning for Conceptual Clustering and Real-time Process Monitoring
- Automatic Extraction of Knowledge Rules from Process Operational Data
- Inferential Models and Software Sensors
- Concluding Remarks
- Appendices: The Continuous Stirred Tank Reactor; The Residue Fluid Catalytic Cracking Process; The Methyl Tertiary Butyl Ether Process
Bibliographische Angaben
- Autor: Xue Z. Wang
- 2012, Softcover reprint of the original 1st ed. 1999, XVIII, 251 Seiten, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 1447111370
- ISBN-13: 9781447111375
Sprache:
Englisch
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