DOI:https://doi.org/10.15407/kvt194.04.041
Kibern. vyčisl. teh., 2018, Issue 4 (194), pp.
Stepashko V.S., DSc (Engineering), Professor,
Head of Dep. for Information Technologies of Inductive Modeling
e-mail: stepashko@irtc.org.ua
International Research and Training Center for Information Technologies
and Systems of the National Academy of Sciences of Ukraine
and Ministry of Education and Science of Ukraine,
Acad. Glushkov av., 40, Kyiv, 03187, Ukraine
FORMATION AND DEVELOPMENT OF SELF-ORGANIZING INTELLIGENT TECHNOLOGIES OF INDUCTIVE MODELING
Introduction. Effective solution of control and decision-making tasks in complex systems should use the results of mathematical modeling. To construct adequate predictive models, many modern methods and tools are available which may be generally based on two principal approaches: theory-driven (deductive) and data-driven (inductive) ones. The data-driven methods are basic for solving typical tacks of data mining; they implement an inductive process of transition from particular data to models generalizing the data. Among all such methods, very notable are those being developed within the area of GMDH-based inductive modeling founded several decades ago by academician O.H. Ivakhnenko.
The purpose of this paper is analysing the background of the GMDH invention by Ivakhnenko and the evolution of model self-organization ideas, methods and tools during the half-century historical period of successful development of the inductive modeling methodology.
Results. Professor Ivakhnenko acquired broad knowledge in the areas of automatic control, engineering cybernetics and emerging neuroscience initiated by the idea of percep-tron. These were those prerequisites which helped Ivakhnenko to synthesize his original self-organizing approach to solving tasks of constructing models of objects and processes on the basis of experimental data. The paper tracks evolution of scientific ideas and views of Ivakhnenko and main achievements in development of GMDH during the period 1968-1997. Contributions of researchers from different countries to the GMDH modification and application are characterized. Results of further developments of inductive modeling meth-ods and tools in the ITIM department are presented and the most promising prospects of in-vestigations in this field are indicated.
Conclusions. Main prerequisites facilitating the creation of the GMDH by O.H. Ivakhnenko were analysed, basic fundamental, technological and applied achievements of the half-century development of inductive modeling both in Ukraine and abroad were characterized, as well as the most prospective ways of further research were formulated.
Keywords: mathematical modeling, data-driven modeling, model self-organization, GMDH, inductive modeling, noise-immune modeling, information technology, case study.
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Received 20.09.2018