Bacterial memetic algorithm for fuzzy rule base optimization
In our previous works model identification methods were discussed. The bacterial evolutionary algorithm for extracting a fuzzy rule base from a training set was presented. The LevenbergMarquardt method was also proposed for determining membership functions in fuzzy systems. The combination of evolutionary and gradient-based learning techniques - the bacterial memetic algorithm - was also introduced. In this paper an improvement of the bacterial memetic algorithm is shown for fuzzy rule...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of World Automation Conference 2006|
|01_Cabrita_Bacterial_memetic_algorithm_2006.pdf||597.97 kB||Adobe PDF|
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