An intelligent rolling prediction method of wind speed along a railway based on wind direction

A technology of wind speed forecasting and rolling forecasting, applied in forecasting, instruments, biological neural network models, etc., to achieve the effect of improving forecasting accuracy

Active Publication Date: 2019-01-11
CENT SOUTH UNIV
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Problems solved by technology

Aiming at the problem of high wind on the railway, most researchers focus on the prediction of wind speed along the railway, aiming to realize high-precision pre

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  • An intelligent rolling prediction method of wind speed along a railway based on wind direction
  • An intelligent rolling prediction method of wind speed along a railway based on wind direction
  • An intelligent rolling prediction method of wind speed along a railway based on wind direction

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Embodiment Construction

[0067] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0068] Such as figure 1 with figure 2 As shown, an intelligent rolling prediction method of wind speed along the railway that integrates wind direction includes the following steps:

[0069] Step 1: Set up wind measuring stations at railway target wind measuring points, including target wind measuring stations and auxiliary wind measuring stations;

[0070] Such as image 3 As shown, the target wind measuring station is 1, 100 meters away from the railway target wind measuring point, and the auxiliary wind measuring stations include 3, arranged at the three vertices of an equilateral triangle, with a distance of 1000 meters between each other, etc. The center of the side triangle is located at the target wind station, and the base is parallel to the railway track.

[0071] Step 2: Construct training sample data;

[0072] Collect the wind speed dat...

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Abstract

The invention discloses an intelligent rolling prediction method of wind speed along a railway based on wind direction. A number of high-precision wind speed forecasting models are established by historical wind speed, and the optimized forecasting results are integrated. The forecasting accuracy and stability of the wind speed forecasting model are improved and the robustness of the wind speed forecasting process is increased by the method of optimal integration and correlation analysis. At the same time, a correction model of wind speed prediction error is establish by using the simulation prediction error and the real wind direction value of the target wind measurement point, so as to greatly improve the wind speed prediction accuracy along the railway line; the wind speed prediction process fuses wind direction data, constructs the mapping relationship between wind speed prediction error and wind direction, and optimizes the wind speed after integrated optimization according to different wind directions, thus avoiding the limitation of single data driving, perfecting the wind speed prediction process along the railway, and significantly improving the wind speed prediction accuracy.

Description

technical field [0001] The invention belongs to the field of railway wind speed prediction, and in particular relates to an intelligent rolling prediction method of wind speed along a railway that integrates wind direction. Background technique [0002] Strong winds seriously threaten the operation safety of railway transportation, and there are many safety accidents caused by sudden strong winds every year. Aiming at the problem of high wind on the railway, most researchers focus on the prediction of wind speed along the railway, aiming to realize high-precision prediction of wind speed along the railway through the analysis of wind speed time series, and rarely involve the error correction problem after the prediction is completed. [0003] In addition to the wind speed, the factors causing train accidents are also closely related to the wind direction of the strong wind. At the same running speed, the running state of the train has a high correlation with the wind directi...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/30G06N3/04
CPCG06Q10/04G06Q50/30G06N3/045
Inventor 刘辉吴海平陈浩林
Owner CENT SOUTH UNIV
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