Control Systems and Computers, N2, 2017, Article 5
DOI: https://doi.org/10.15407/usim.2017.02.058
Upr. sist. maš., 2017, Issue 2 (268), pp. 5873.
UDC 621.513.8
Stepashko Volodymyr S., Doctor of Eng. Sciences, Head of the department, International Research and Training Center for Information Technologies and Systems NAS and MES of Ukraine, Glushkov ave., 40, Kyiv, 03187, Ukraine, Email: stepashko@irtc.org.ua
The Achievements and Prospects of Inductive Modeling
Introduction. Inductive modelling as the scientific school was formed by academician Alexey Ivakhnenko and is still actively being developed. The worldwide known Group method of data handling (GMDH) as a means of selforganizing models keeps the central place in this studying. The concept “inductive modelling” can be defined as a selforganizing process of evolutionary transition from primary data to mathematical models reflecting patterns of the simulated systems functioning, implicitly contained in the available experimental or statistical data.
Purpose. The typical problems solved by means of inductive modelling are described, information on this scientific school in Ukraine and abroad is presented, the fundamental basic and the technological achievements are defined, the most promising ways of further research are formulated.
Methods. The goal of this article is being achieved by presenting a comprehensive survey of the main publications in this area and structuring the material in accordance with the historical, fundamental, technological and applied aspects of the inductive modelling.
Results. As a result of the references survey in the field of inductive modelling, it can be stated that the GMDH is a promising basis of modern information technology for discovering knowledge from data, or one of original and efficient methods of data mining.
Conclusion. The further development of the model assumes the improvement of the theory of inductive modelling, the development and implementation of new highperformance algorithms in uptodate computer technologies and the application of these technologies to solve a wide range of reallife problems of modelling, forecasting, control and decisionmaking in systems of different fields – economic, ecological, technological and others.
Keywords: Inductive modeling, GMDH, selforganization, structuralparametric identification, data mining, decisionmaking.

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Received 27.04.2017