| Autor: |
Kuftinova, N. G., Ostroukh, A. V., Karelina, M. Yu., Matyukhina, E. N., Akhmetzhanova, E. U. |
| Zdroj: |
Russian Engineering Research; Jun2021, Vol. 41 Issue 6, p536-538, 3p |
| Abstrakt: |
In big data analysis at an enterprise, a useful option is the analysis of spatial data by machine learning, using a hybrid smart system. Machine learning permits complex nonlinear prediction with maximum precision and efficiency. A real-time big data prediction network for effective traffic flow is of great practical value. In such a network, the key problem is to construct an adaptive model on the basic of historical data. Traffic flow prediction is critical to traffic management in information technology. Real-time data proliferation led to the development of big data analysis, for which nonlinearity of traffic data is the main source of inaccurate prediction. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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