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News of the Kabardin-Balkar scientific center of RAS, 2018, Issue 6-3, Pages 132–137
(Mi izkab116)
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COMPUTER SCIENCE. CALCULATION EQUIPMENT. MANAGEMENT
Modeling the forecast of temporal metrics based on method of reverse propagation of errors and optimization heuristics
M. V. Sychugov, Yu. A. Kravchenko, M. I. Anchyokov Southern Federal University
of the Russian Academy of Sciences
347928, Rostov region, Taganrog, Nekrasovsky lane, 44
Abstract:
This article discusses the problem of modeling the time series forecast in the field of mobile development, where you need to have data at what point in time users leave the application to take measures to
increase the lifetime and income level brought by the application.
The proposed algorithm based on a neural network trained by the back propagation method provides
an opportunity to predict different time periods in relation to the number of remaining users in the application. The back propagation method is used in conjunction with heuristics to accelerate convergence and
avoid hitting local minima.
The scientific novelty is represented by the time series forecasting algorithm, which allows to increase
the efficiency of decision-making procedures in intelligent analytical systems. The results of the forecast
are presented for different time intervals, characteristic of the mobile application’s use.
Keywords:
neural networks, method of back propagation, retention of mobile users, forecasting systems, time series.
Received: 11.12.2018
Citation:
M. V. Sychugov, Yu. A. Kravchenko, M. I. Anchyokov, “Modeling the forecast of temporal metrics based on method of reverse propagation of errors and optimization heuristics”, News of the Kabardin-Balkar scientific center of RAS, 2018, no. 6-3, 132–137
Linking options:
https://www.mathnet.ru/eng/izkab116 https://www.mathnet.ru/eng/izkab/y2018/i63/p132
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Abstract page: | 58 | Full-text PDF : | 61 | References: | 8 |
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