Abstract
In the present paper, Genetic Algorithms (GA) have been used to optimize the design of a generic expert system based on fuzzy logics. Using the classical branch-and-bound method, the latter performs a heuristic graph search to solve a decision-making problem under uncertain environment. After building this fuzzy expert system, we isolate a set of parameters which are important for the system efficiency, and we show how these parameters can be optimized `automatically' using Genetic Algorithms. This optimization brings significant improvement over the manual tuning of the parameters in the specific case of a fuzzy expert system developed for the automatic target recognition of armoured vehicles starting from short-range infra-red images.
| Original language | English |
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| Pages | 115-120 |
| Number of pages | 6 |
| Publication status | Published - 1994 |
| Event | Proceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA - San Antonio, TX, USA Duration: 18 Dec 1994 → 21 Dec 1994 |
Conference
| Conference | Proceedings of the 1994 1st International Joint Conference of NAFIPS/IFIS/NASA |
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| City | San Antonio, TX, USA |
| Period | 18/12/94 → 21/12/94 |