Constructing a Metamodel of Inductive Modeling Algorithms
Yevheniya Savchenko-Syniakova, Volodymyr Semenovych Stepashko · 2025
This paper investigates the problem of structuring knowledge in the field of inductive modeling. Inductive modeling algorithms are effective means of automatically constructing models based on experimental data. In this area, the theory of inductive modeling has been developed, new algorithms and software have been developed, and many applied problems in various areas of human activity have been successfully solved. The organization and structuring of knowledge on typical components of inductive modeling algorithms occur within the framework of the development of a metamodel for this area. A general representation of the metamodel is proposed, including sub-metamodels of individual components of the modeling process.