Finding optimal architecture of neural networks for predicting referrals on the virtual museums website
Otabek KhujaevUrgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, UzbekistanOmonboy KhalmuradovUrgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, UzbekistanOrtiq RuzibayevTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Tashkent, UzbekistanSh. Kh. IsmoilovUrgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, UzbekistanKhudayshukur KuzibaevUrgench branch of Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, Urgench, Uzbekistan
2021 International Conference on Information Science and Communications Technologies (ICISCT)conference2021en
ABI
Annotatsiya
This paper presents applying two neural network models for time series prediction problems. focused choosing optimal architecture of Elman and feedforward neural networks for time series prediction. Topics discussed include neural network design, overview methods of forecasting, sliding window method, training and testing of network, training algorithms and all results obtained with neural network toolbox in MATLAB.
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