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 metaevolution...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
This contribution deals with a new idea of how to create evolutionary algorithms by means of symboli...
This research deals with the comparison of three novelty approaches for constant estimation in analy...
This papers' aim is to provide the Artificial Intelligence community with a better tool for symbolic...
This paper proposes a new technique for the estimation of values of constants in programs synthesize...
Tento příspěvek popisuje analytické programování, novou metodu, která umožňuje řešit různé problémy ...
This research deals with a novel approach to classification - pseudo neural networks (PNN). This tec...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
This paper provides a closer insight into applicability and performance of the hybridization of symb...
The chapter will explain the differences in the approach of the metaevolution. Metaevolution as well...
In this paper we discuss alternative tool for symbolic regression so called Analytical programming a...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
This contribution deals with a new idea of how to create evolutionary algorithms by means of symboli...
This research deals with the comparison of three novelty approaches for constant estimation in analy...
This papers' aim is to provide the Artificial Intelligence community with a better tool for symbolic...
This paper proposes a new technique for the estimation of values of constants in programs synthesize...
Tento příspěvek popisuje analytické programování, novou metodu, která umožňuje řešit různé problémy ...
This research deals with a novel approach to classification - pseudo neural networks (PNN). This tec...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
This paper provides a closer insight into applicability and performance of the hybridization of symb...
The chapter will explain the differences in the approach of the metaevolution. Metaevolution as well...
In this paper we discuss alternative tool for symbolic regression so called Analytical programming a...
This research deals with the hybridization of symbolic regression open framework, which is Analytica...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
In the known methods of symbolical regression by search of the solution with the help of a genetic a...
This contribution deals with a new idea of how to create evolutionary algorithms by means of symboli...