DOI: 10.17587/prin.13.301-308

Decision Support System based on Application of the Second Generation Neural Network

E. V. Palchevsky, Lecturer, teelxp@inbox.ru, Financial University under the Government of the Russian Federation, Moscow, 125167, Russian Federation, V. V. Antonov, Professor, antonov.v@bashkortostan.ru, Ufa State Aviation Technical University, Ufa, 450008, Russian Federation

Corresponding author: Palchevsky Evgeniy V., Lecturer, Financial University under the Government of the Russian Federation, Moscow, 125167, Russian Federation, E-mail: teelxp@inbox.ru

The issue of the feasibility of using existing statistical and hydrological methods for short-term and early forecasting in the framework of forecasting the levels of water rise in water bodies is considered: a comparative review is given, which describes their advantages and disadvantages. In the course of analyzing the shortcomings of these methods, the problem of operational and early (advance) forecasting of water rise levels was identified. To solve this problem, a decision support system is proposed for predicting the water rise levels in advance, based on a neural network (intelligent) analysis of retrospective data (date, water level, air temperature, atmospheric pressure and wind speed) to calculate the water level values for 5 days in advance. The artificial neural network itself is based on the freely distributed library of machine learning programs "TensorFlow", and a modified backpropagation method is used as training, the main difference of which is an increase in the learning rate of an artificial neural network. The results of the analysis of the effectiveness showed that the proposed decision support system is more accurate (the error between the real and calculated values does not exceed 2.10 %), compared to existing common methods/systems (8.36 %). This will allow to give the necessary time to special services for the implementation of flood control measures to prepare for the protection of technical facilities of enterprises.

Keywords: forecasting, intellectual analysis, neural network analysis, retrospective data, data mining, forecasting water levels

pp. 301–308

For citation:
Palchevsky E. V., Antonov V. V. Decision Support System based on Application of the Second Generation Neural Network, Programmnaya Ingeneria, 2022, vol. 13, no. 6, pp. 301—308.

The study is conducted with financial support from the Ministry of Education and Science of the Russian Federation as part of the basic part of the state assignment to higher education educational institutions # FEUE-2020-0007. The article was based on the materials of the report at the IX All-Russian Scientific Conference "Information Technologies for Intelligent Decision Support" ITIDS-2021.