@inbook{7f0ae77040e647cd9d8f610de0f3e117,
title = "Genetic algorithms",
abstract = "This chapter introduces the basic concepts and notation of genetic algorithms, which is a basic search methodology that can be used for modelling and simulation of complex non-linear dynamical systems. Since this technique can be considered as general purpose optimization methodologies, we can use them to find the mathematical model which minimizes the fitting errors for a specific problem. On the other hand, we can also use this technique for simulation if we exploit their efficient search capabilities to find the appropriate parameter values for a specific mathematical model. We can use a genetic algorithm to optimize the number of rules or the membership functions of a fuzzy system for a specific problem. These are two important application of genetic algorithms, which will be used in later chapters to design intelligent systems for controlling real-world dynamical systems.",
author = "Oscar Castillo and Aguilar, {Luis T.}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.",
year = "2019",
doi = "10.1007/978-3-030-03134-3_2",
language = "Ingl{\'e}s",
series = "Studies in Fuzziness and Soft Computing",
publisher = "Springer Verlag",
pages = "23--39",
booktitle = "Studies in Fuzziness and Soft Computing",
address = "Alemania",
}