Different Approaches For Constant Estimation In Analytic Programming

This research deals with different approaches for constant estimation in analytic programming (AP). AP is a tool for symbolic regression tasks which enables to synthesise an analytical solution based on the required behaviour of the system. Some tasks do not need any constant estimation AP is used in its basic version without any constant estimation handling. Compared to this, cases like data approximation need constants (coefficients) which are essential for the process of precise solution synthesis. This paper offers another strategy to already known and used by the AP from the very beginning and approaches published recently in 2016. This paper compares these procedures and the discussion also includes nonlinear fitting and metaevolutionary approach. As the main evolutionary algorithm, a differential algorithm (de/rand/1/bin) for the main process of AP is used.