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Publications in Math-Net.Ru
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Combined application of recurrent neural networks and statistical methods for improved oceanographic data forecasting accuracy
Intelligent systems. Theory and applications, 26:1 (2022), 241–245
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Method for improving accuracy of neural network forecasts based on probability mixture models and its implementation as a digital service
Inform. Primen., 15:3 (2021), 63–74
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Analysis of configurations of LSTM networks for medium-term vector forecasting
Inform. Primen., 14:1 (2020), 10–16
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Application of recurrent neural networks to forecasting the moments of finite normal mixtures
Inform. Primen., 13:3 (2019), 114–121
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Optimization of hyperparameters of neural networks using high-performance computing for prediction of precipitation
Inform. Primen., 13:1 (2019), 75–81
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Forecasting moments of finite normal mixtures using feedforward neural networks
Sistemy i Sredstva Inform., 28:3 (2018), 62–71
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MSM Tools as a heterogeneous computing service
Sistemy i Sredstva Inform., 27:1 (2017), 60–72
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Application of the CUDA architecture for implementation of grid-based algorithms for the method of moving separation of mixtures
Sistemy i Sredstva Inform., 26:4 (2016), 60–73
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Stability of finite mixtures of generalized gamma-distributions with respect to disturbance of parameters
Inform. Primen., 5:1 (2011), 31–38
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