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@inproceedings{63321, author = {Guchenkoa, Mykola and Sokhin, Natalya and Skalsky, Anton and Bartuška, Ladislav and Čejka, Jiří}, address = {Amsterdam, The Netherlands}, booktitle = {Transportation Research Procedia}, edition = {Volume 44}, editor = {Stopková, M., Bartuška, L. Stopka, O.}, keywords = {traffic control; forecasting method; local model of controlled process}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Amsterdam, The Netherlands}, pages = {78-85}, publisher = {Elsevier B.V., Radarweg 29, 1043 NX Amsterdam, The Netherlands}, title = {Research of Prognostic Abilities of Local Model of Controlled Process for Traffic Forecasting}, url = {https://www.sciencedirect.com/science/article/pii/S2352146520300624}, year = {2020} }
TY - JOUR ID - 63321 AU - Guchenkoa, Mykola - Sokhin, Natalya - Skalsky, Anton - Bartuška, Ladislav - Čejka, Jiří PY - 2020 TI - Research of Prognostic Abilities of Local Model of Controlled Process for Traffic Forecasting PB - Elsevier B.V., Radarweg 29, 1043 NX Amsterdam, The Netherlands CY - Amsterdam, The Netherlands KW - traffic control KW - forecasting method KW - local model of controlled process UR - https://www.sciencedirect.com/science/article/pii/S2352146520300624 N2 - "The problem of traffic forecasting is analyzed. It is shown that the characteristic feature of transport flows is their nonstationarity. Prognostication of traffic by synthesis of local model of controlled process (LMCP) is proposed and the forecasting method is presented. The advantages of LMCP are the simplicity of mathematical apparatus and the possibility of organizing control in conditions of complexity, uncertainty and non-stationarity of the controlled process. The active accumulation of information about the controlled process in the process of LMCP synthesizing allows to reduce the problem of forecasting with known input and output and unknown external influences to the problem of forecasting with known input and output and absence of external influences, regardless of their number. Therefore, the offered method allows real time traffic forecasting, without the need for preliminary accumulation, processing and analysis of large amounts of data. The obtained results can be used to solution of practical problems arising in traffic control, in particular, to increase the throughput of highways, to reduce congestions and accelerate transport flows." ER -
GUCHENKOA, Mykola, Natalya SOKHIN, Anton SKALSKY, Ladislav BARTUŠKA a Jiří ČEJKA. Research of Prognostic Abilities of Local Model of Controlled Process for Traffic Forecasting. In Stopková, M., Bartuška, L. Stopka, O. \textit{Transportation Research Procedia}. Volume 44. Amsterdam, The Netherlands: Elsevier B.V., Radarweg 29, 1043 NX Amsterdam, The Netherlands. s.~78-85, 386 s. ISSN~2352-1457. 2020.
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