**2.6 Adaptive neuro-fuzzy inference system (ANFIS)**

The disadvantages of fuzzy inference systems and neural networks are the reason why the neuro-fuzzy systems appeared, retaining the advantages of both methods and outweighing the disadvantages. The lack of fuzzy inference systems is solved by creating the knowledge about a problem from the neural inference system training data, while the complicated and hard-to-understand rules of neural networks are bypassed by using linguistic variables by means of which results are easily explained. A well-known neuro-fuzzy system is the adaptive neuro-fuzzy inference system (ANFIS) used in solving various problems. The fuzzy inference system of Sugeno type can be considered as an adaptive neuro-fuzzy inference system in the form similar to neural networks in which by training the system on input/output data set, the parameters of the fuzzy inference membership functions or antecedent parameters and the parameters of the Sugeno fuzzy system output function or consequent parameters (pi, qi i ri) are adapted [13].
