| 書目名稱 | Data Mining and Knowledge Discovery for Process Monitoring and Control |
| 編輯 | Xue Z. Wang |
| 視頻video | http://file.papertrans.cn/263/262934/262934.mp4 |
| 概述 | Features the subjects of on-line signal preprocessing, feature extraction and concept formation, operational state identification and automatic generation of decision trees and production rules from d |
| 叢書名稱 | Advances in Industrial Control |
| 圖書封面 |  |
| 描述 | 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. |
| 出版日期 | Book 1999 |
| 關鍵詞 | Artificial Intelligence; Control; Control Applications; Control Engineering; Data Mining; Fuzzy; Knowledge |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4471-0421-6 |
| isbn_softcover | 978-1-4471-1137-5 |
| isbn_ebook | 978-1-4471-0421-6Series ISSN 1430-9491 Series E-ISSN 2193-1577 |
| issn_series | 1430-9491 |
| copyright | Springer-Verlag London 1999 |
|Archiver|手機版|小黑屋|
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