Comparative Study of Bio-inspired Algorithms Applied in the Optimization of Fuzzy Systems.

In the medical area, it is very important to have accurate results in diagnosis of diseases that people may suffer. This is why, there is a need to perform the optimization of the fuzzy classifier which provides the nocturnal blood pressure profile of patients, and which is important, due that with this diagnosis we may know if the patient is prone to have a cardiovascular event. This fuzzy system is designed using different membership functions, which are trapezoidal and Gaussian membership functions, in order to select the fuzzy system that provides better results when making the classification. Two bioinspired algorithms are used separately to test their performance, which are the Crow Search Algorithm and Chicken Swarm Optimization. Thirty experiments were performed varying the parameters in the algorithms and from which it can be concluded that the CSO provides better results when optimizing fuzzy systems with both types of membership functions.