PNIPU: Data Mining Virtual Environment

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2022: Solution Development

Scientists Perm Polytechnic are developing virtual a convenient environment for mining, data which will become an assistant for business analysts data analysts. The university announced this on August 19, 2022.

Leonid Kozhemyakin, a graduate of the graduate school of the Department of Applied Mathematics of the Perm National Research Polytechnic University, as well as Alexander Makkaveev, a specialist in highly efficient computing technologies, senior system designer of CFT CJSC, took part in the creation of the virtual environment.

The peculiarity of the data processing technology lies in the fact that now there is no need to go through hundreds and thousands of options for possible structures of the neural network when searching for a suitable one, the optimal structure is determined on the basis of preliminary data processing using specially developed methods. The user will be able to download his data and at the output get an answer to the question - there are patterns in his data or not. If patterns are found, then the possibility of finding management decisions will open, relying on the causal relationships found in the source data, told 'Candidate of Economic Sciences, Associate Professor, Head of the Department of Organization of Scientific Research Alexander Alekseev. '

The user will not need to install additional software on his computer, since the system will be implemented on a client-server architecture, so that all information processing will be carried out on the server.

The designed system is not tied to any subject area, so the project software product developed within the framework can be used as a universal platform for creating application solutions in the field,, medicine, and finance industries oils and gas productions other sectors. economies reported 'Candidate of Physical and Mathematical Sciences, Associate Professor of the Department of Computational Mathematics, Mechanics and Biomechanics Vladislav Nikitin. '

According to polytechnics, an important advantage of this technology is explainability - you can give a clear interpretation to each neuron on each hidden layer. This expands the possibilities for the introduction of neural network technologies. The project received support from a large IT company, ready to buy a license to use the software product after the completion of all stages of R&D.