LAUSR

Abstract Hepatitis C is a liver disease caused by hepatitis C virus. Prevalence of the disease among people and spread of it in the society is becoming an important concern in epidemiology. In this study an ANFIS-based optimal control is developed to control hepatitis C virus epidemic. Genetic Algorithm has employed to select optimal control inputs based on the initial population of the different compartments and this process is repeated for several different initial conditions in order to create a set of data. Prepared data were used as input for ANFIS to train coefficients of Takagi-Sugeno fuzzy structure and finally this structure is used as the controller. Taking advantages of the proposed method, decreased population of the infected classes significantly in comparison with no control case. Moreover, employing our strategy decreased value of objective function about 16% with respect to past strategies which introduced in the literature.