Prof. Yedilkhan Amirgaliyev

Institute of Information and Computing Technologies, Almaty, Kazakhstan


Data-driven approaches and their industrial application


Abstract. Methods of data mining are developed for many scientific areas and therefore contain different patter of the specifics of these disciplines. Moreover, these methods are currently widely used in different industry areas. The data mining algorithms can generate different solutions for the same data, which motivates scientists to improve it. The main goal of mining methods is to search for existing structures, patterns, and features in the collected data. Historical data from various sources make it possible to model complex processes in energy generation in renewable energy sources such as solar heliocollectors and biogas plants, automate the process of interpreting geophysical data, and assess soil salinity using remote sensing data.

Plenary Speakers

Prof. Roman A. Polyak
George Mason University, USA
Prof. Srinivas Chakravarthy
Kettering University, Flint, USA
Prof. Arkadii Chikrii
V. M. Glushkov Institute of Cybernetics, Kyiv, Ukraine
Prof. Boris S. Mordukhovich
Wayne State University, Detroit, USA
Prof. Janusz Kacprzyk
Warsaw University of Technology, Poland
Prof. Yedilkhan Amirgaliyev
Institute of Information and Computing Technologies, Almaty, Kazakhstan
Prof. Adil Bagirov
Centre for Smart Analytics, Institute of Innovation, Science and Sustainability, Federation University Australia, Australia
Prof. Rza Bashirov
Eastern Mediterranean University, Turkey
Prof. Refail Kasimbeyli
Eskişehir Technical University, Türkiye
Prof. Agasi Melikov
Institute of Control Systems, Ministry of Science and Education, Azerbaijan
Prof. Mais Farkhadov
Institute of Control Sciences of RAS, Russia