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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wu, Xianchun Cinar, Ali |
| Copyright Year | 1992 |
| Description | Author affiliation: Department of Chemical Engineering, Illinois Institute of Technology, Chicago, IL 60616 (Wu, Xianchun) || Department of Chemical Engineering, Illinois Institute of Technology, Chicago, IL 60616. Fax:(312)567-8874 checinar@minna.iit.edu (Cinar, Ali) |
| Abstract | Development of input-output models for nonlinear systems have gained attention recently. A knowledge-based system (KBS) is being developed for constructing input-output models of nonlinear dynamic processes. The KBS automates outlier detection and triggers the execution of advanced nonparametric modeling techniques, such as parsimonious polynomial approximation and multivariable adaptive regression splines. The software combines heuristic search methods and reasoning ability of the KBS with statistical inferences to detect outliers, determine the nonlinearity of the system, identify the nonlinear or linear models and validate them automatically. |
| Starting Page | 1447 |
| Ending Page | 1448 |
| File Size | 191783 |
| Page Count | 2 |
| File Format | |
| ISBN | 0780302109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1992-06-24 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | American Automatic Control Council(AACC) |
| Subject Keyword | Knowledge based systems Autoregressive processes Nonlinear dynamical systems Nonlinear systems Chemical engineering Chemical technology Polynomials Search methods Linear systems Process control |
| Content Type | Text |
| Resource Type | Article |
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