Abstract
The major problem in building qualitative models via on-line qualitative system identification is how to filter the spurious constraints that are generated from the qualitative reasoning technique. This paper proposes a solution to this problem by an integration of genetic algorithms (GA) and qualitative reasoning. The paper will demonstrate the use of qualitative reasoning to partition the input quantity space into different subsystems, and implementation of GAs to filter and optimize the predicted constraints. The proposed method is verified by simulated examples that suggest the algorithm converges to the optimal point with high speed.
Original language | English |
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Pages (from-to) | 415-431 |
Number of pages | 17 |
Journal | Simulation Practice and Theory |
Volume | 8 |
Issue number | 6-7 |
DOIs | |
Publication status | Published - 15 Mar 2001 |
Keywords
- Genetic algorithms
- Model identification
- Qualitative models