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Application of Large-Scale Database-Based Online Modeling to Plant State Long-Term Estimation
- Source :
- IEEJ Transactions on Electronics, Information and Systems. 131:718-721
- Publication Year :
- 2011
- Publisher :
- Institute of Electrical Engineers of Japan (IEE Japan), 2011.
-
Abstract
- Recently, attention has been drawn to the local modeling techniques of a new idea called “Just-In-Time (JIT) modeling”. To apply “JIT modeling” to a large amount of database online, “Large-scale database-based Online Modeling (LOM)” has been proposed. LOM is a technique that makes the retrieval of neighboring data more efficient by using both “stepwise selection” and quantization. In order to predict the long-term state of the plant without using future data of manipulated variables, an Extended Sequential Prediction method of LOM (ESP-LOM) has been proposed. In this paper, the LOM and the ESP-LOM are introduced.
- Subjects :
- Estimation
Database
Computer science
business.industry
Machine learning
computer.software_genre
Term (time)
Plant state
Sequence prediction
Data mining
State (computer science)
Artificial intelligence
Electrical and Electronic Engineering
Long-term prediction
Scale (map)
Quantization (image processing)
business
computer
Subjects
Details
- ISSN :
- 13488155 and 03854221
- Volume :
- 131
- Database :
- OpenAIRE
- Journal :
- IEEJ Transactions on Electronics, Information and Systems
- Accession number :
- edsair.doi...........3c0e88090a787728266adcaad4a76c0f
- Full Text :
- https://doi.org/10.1541/ieejeiss.131.718