{"id":2085,"date":"2023-09-23T14:44:57","date_gmt":"2023-09-23T09:44:57","guid":{"rendered":"http:\/\/vestnik.polytech.tj\/?p=2085"},"modified":"2023-10-26T19:55:19","modified_gmt":"2023-10-26T14:55:19","slug":"%d0%bc%d0%be%d0%b4%d0%b5%d0%bb%d0%b8%d1%80%d0%be%d0%b2%d0%b0%d0%bd%d0%b8%d0%b5-%d0%b2%d1%80%d0%b5%d0%bc%d0%b5%d0%bd%d0%bd%d1%8b%d1%85-%d1%80%d1%8f%d0%b4%d0%be%d0%b2-%d1%81-%d0%bf%d0%be%d0%bc%d0%be","status":"publish","type":"post","link":"https:\/\/vestnik.polytech.tj\/?p=2085&lang=ru","title":{"rendered":"\u041c\u041e\u0414\u0415\u041b\u0418\u0420\u041e\u0412\u0410\u041d\u0418\u0415 \u0412\u0420\u0415\u041c\u0415\u041d\u041d\u042b\u0425 \u0420\u042f\u0414\u041e\u0412 \u0421 \u041f\u041e\u041c\u041e\u0429\u042c\u042e \u041c\u0415\u0422\u041e\u0414\u0410  \u041d\u0410\u0418\u041c\u0415\u041d\u042c\u0428\u0418\u0425 \u041a\u0412\u0410\u0414\u0420\u0410\u0422\u041e\u0412"},"content":{"rendered":"<h4><strong>\u0410\u0432\u0442\u043e\u0440\u044b<\/strong><\/h4>\n<p>&nbsp;<\/p>\n<p><strong>\u041d\u0438\u0437\u0430\u043c\u0438\u0442\u0434\u0438\u043d\u043e\u0432 \u0410.\u0418. <\/strong>\u2013 <em>\u0434\u043e\u043a\u0442\u043e\u0440 \u0444\u0438\u043b\u043e\u0441\u043e\u0444\u0438\u0438 \u043f\u043e \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u0438 (<\/em><em>PhD<\/em><em>), \u0441\u0442\u0430\u0440\u0448\u0438\u0439 <\/em><em>\u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u0442\u0435\u043b\u044c<\/em><em>,<\/em><em> \u043a\u0430\u0444\u0435\u0434\u0440\u0430 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0435\u0445 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0439, 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<em>\u043c\u0430\u0433\u0438\u0441\u0442\u0440\u0430\u043d\u0442,<\/em> <em>\u041f\u043e\u043b\u0438\u0442\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0438\u043d\u0441\u0442\u0438\u0442\u0443\u0442<\/em> <em>\u0422\u0430\u0434\u0436\u0438\u043a\u0441\u043a\u043e\u0433\u043e <\/em><em>\u0442\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u0430 \u0438\u043c\u0435\u043d\u0438 \u0430\u043a\u0430\u0434\u0435\u043c\u0438\u043a\u0430 \u041c.\u0421. \u041e\u0441\u0438\u043c\u0438,<\/em><em> \u0433. \u0425<\/em><em>\u0443\u0434\u0436\u0430\u043d\u0434, <\/em><em>\u0420\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0430 \u0422\u0430\u0434\u0436\u0438\u043a\u0438\u0441\u0442\u0430\u043d<\/em><em>, <\/em><a href=\"mailto:lashena_t@mail.ru\"><em>lashena<\/em><em>_<\/em><em>t<\/em><em>@<\/em><em>mail<\/em><em>.<\/em><em>ru<\/em><\/a><\/p>\n<p><em>\u00a0<\/em><\/p>\n<h4><strong><em>\u0410\u043d\u043d\u043e\u0442\u0430\u0446\u0438\u044f<\/em><\/strong><\/h4>\n<p>&nbsp;<\/p>\n<p><em>\u00a0\u0414\u043b\u044f \u043f\u043e\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u044f \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432\u0440\u0435\u043c\u0435\u043d\u043d\u044b\u0445 \u0440\u044f\u0434\u043e\u0432, \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0447\u0430\u0441\u0442\u043e \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0435\u043c\u044b\u043c\u0438 \u0433\u0440\u0443\u043f\u043f\u0430\u043c\u0438 \u043c\u0435\u0442\u043e\u0434\u043e\u0432, \u044f\u0432\u043b\u044f\u044e\u0442\u0441\u044f \u0434\u0435\u0442\u0435\u0440\u043c\u0438\u043d\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u043c\u043e\u0434\u0435\u043b\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435, 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\u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u043b\u0438\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u044b<\/em><\/strong><\/h4>\n<h4>\u00a0<\/h4>\n<ol>\n<li><em> Nizamitdinov, M. Memmedli, O. Ozdemir (2010) Comparison Study Of P-Spline and Univariate Additive Model (Cubic Smoothing Spline) In Time-Series Prediction, In Proceedings: International Conference 24th Mini EURO Conference \u201cContinuous Optimization and Information-Based Technologies in the Financial Sector\u201d (MEC EurOPT 2010), Izmir, TURKEY(2010), P.<\/em> <em>34<\/em> <em>\u2013<\/em> <em>39<\/em><em>.<\/em><\/li>\n<li><em>Nizamitdinov, M. Memmedli, O. Ozdemir (2010), Time Series Forecasting using Fuzzy Time Series Approach, Neural Network Models and Regression Splines \u0447\u043e\u043f\u04e3 In Abstract Book: 24th European Conference on Operational Research, Lisbon, Portugal, (2010), P. 257<\/em><em>.<\/em><\/li>\n<li><em>Nizamitdinov, M. Memmedli, O. Ozdemir (2013), ANN models and bayesian spline models for analysis of exchange rates and gold price. International Econometric Review, 5(2), <\/em><em>\u0420. <\/em><em>53<\/em> <em>\u2013<\/em> <em>69.<\/em><\/li>\n<li><em>Nizamitdinov, A. Shamilov, Forecasting time series data with spline functions, In Proceedings: The 17th International Symposium on Econometrics, Operations Research and Statistics, Sivas, Turkey, (2016), P.<\/em> <em>360<\/em> <em>\u2013<\/em><em> 3<\/em><em>61<\/em><em>.<\/em><\/li>\n<li><em>Nizamitdinov, Ozer Ozdemir, Neuro approaches and spline models in time series analysis, In Proceedings: The 17th International Symposium on Econometrics, Operations Research and Statistics, Sivas, Turkey, (2016), P.<\/em> <em>366<\/em> <em>\u2013<\/em> <em>367<\/em><em>.<\/em><\/li>\n<li><em>Abraham B. (1981). Missing Observations in Time Series. Communications in statistics Theory A, 10, <\/em><em>\u0420. <\/em><em>1643<\/em> <em>\u2013<\/em><\/li>\n<li><em>Beveridge S. (1992). Least Squares Estimation of Missing Values in Time Series.<\/em><\/li>\n<li><em>Brockwell P.J., &amp; Davis, R. A. (1991). Time Series: Theory and Methods. New York, USA: Springer-Verlag.<\/em><\/li>\n<li><em>Chatfield C. (2003). The Analysis of Time Series: An Introduction (6thed.). New York, USA: John Wiley and Sons.<\/em><\/li>\n<li><em>Damsleth E. (1979). Interpolating Missing Values in a Time Series. Scand J Statist., 7, <\/em><em>\u0420. <\/em><em>33<\/em> <em>\u2013<\/em><\/li>\n<li><em>Ferreiro O. (1987). Methodologies for the Estimation of Missing Observations in Time Series. Statistics &amp; Probability Letters, 5(1), <\/em><em>\u0420. <\/em><em>65<\/em> <em>\u2013<\/em><\/li>\n<li><em>Gardner G., Harvey A.C. &amp; Phillips, G. D. A. (1980). An Algorithm for Exact Maximum Likelihood Estimation of Autoregressive-Moving Average Models by Means of Kalman. Applied Statistics, 29, <\/em><em>\u0420. <\/em><em>311<\/em> <em>\u2013<\/em><\/li>\n<\/ol>\n<h4>\u00a0<\/h4>\n<h4><strong>\u0414\u0430\u0442\u0430 \u043f\u0443\u0431\u043b\u0438\u043a\u0430\u0446\u0438\u044f<\/strong><\/h4>\n<p>2023-10-26<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0410\u0432\u0442\u043e\u0440\u044b &nbsp; \u041d\u0438\u0437\u0430\u043c\u0438\u0442\u0434\u0438\u043d\u043e\u0432 \u0410.\u0418. \u2013 \u0434\u043e\u043a\u0442\u043e\u0440 \u0444\u0438\u043b\u043e\u0441\u043e\u0444\u0438\u0438 \u043f\u043e \u0441\u043f\u0435\u0446\u0438\u0430\u043b\u044c\u043d\u043e\u0441\u0442\u0438 (PhD), \u0441\u0442\u0430\u0440\u0448\u0438\u0439 \u043f\u0440\u0435\u043f\u043e\u0434\u0430\u0432\u0430\u0442\u0435\u043b\u044c, \u043a\u0430\u0444\u0435\u0434\u0440\u0430 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u043c\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u044f \u0438 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u043e\u043d\u043d\u044b\u0435\u0445 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0439, \u041f\u043e\u043b\u0438\u0442\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u0438\u0439 \u0438\u043d\u0441\u0442\u0438\u0442\u0443\u0442 \u0422\u0430\u0434\u0436\u0438\u043a\u0441\u043a\u043e\u0433\u043e \u0442\u0435\u0445\u043d\u0438\u0447\u0435\u0441\u043a\u043e\u0433\u043e \u0443\u043d\u0438\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442\u0430 \u0438\u043c\u0435\u043d\u0438\u00a0 \u0430\u043a\u0430\u0434\u0435\u043c\u0438\u043a\u0430 \u041c.\u0421. \u041e\u0441\u0438\u043c\u0438, \u0433. \u0425\u0443\u0434\u0436\u0430\u043d\u0434, \u0420\u0435\u0441\u043f\u0443\u0431\u043b\u0438\u043a\u0430 \u0422\u0430\u0434\u0436\u0438\u043a\u0438\u0441\u0442\u0430\u043d, ahlidin@gmail.com \u041b\u0430\u0448\u0435\u043d\u0430 \u0422.\u0412. &#8212; 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