Application and comparison of intelligent algorithms to solve the fractional heat conduction inverse problem

This paper describes an application of intelligent algorithms to reconstruct the boundary condition of second kind in the fractional heat conduction equation. For this purpose, a functional defining error of approximate solution was minimized. To minimize this functional two Ant Colony Optimization (ACO) algorithms were used and compared. To reduce computational time, calculations has been performed in parallel way (multi-threaded). The paper presents examples to illustrate the accuracy and stability of the presented algorithms.