Bacterial type algorithms used for fuzzy rule base extraction

László Gál,

Rita Lovassy,

László T. Kóczy

Abstrakt

The paper gives an overview of various bacterial type evolutionary algorithms used for fuzzy rule based identification. In order to find an optimal rule base from the input-output training data set, several improved algorithms have been developed in recent years. The task is to increase the models’ accuracy and convergence speeds by modifying a part of the Mamdani-type inference system.

Słowa kluczowe: FRBI, pseudo-bacterial genetic algorithm, bacterial evolutionary algorithm, bacterial memetic algorithm with memetic mutation, progressive bacterial algorithm