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A multi-model and multi-feature fusion method for wind speed prediction along high-speed railway

A multi-feature fusion, high-speed railway technology, applied in forecasting, computational models, neural learning methods, etc., can solve problems such as unstable prediction effect of a single model

Active Publication Date: 2017-10-13
CENT SOUTH UNIV
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Problems solved by technology

At the same time, due to the reliability problems of hardware equipment, the prediction effect of a single model is unstable, and the wind speed prediction data along the railway line is not allowed to interrupt the output, so the wind speed prediction along the railway line must have stable performance and be able to output high precision continuously under various abnormal conditions forecast data

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  • A multi-model and multi-feature fusion method for wind speed prediction along high-speed railway
  • A multi-model and multi-feature fusion method for wind speed prediction along high-speed railway
  • A multi-model and multi-feature fusion method for wind speed prediction along high-speed railway

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Embodiment Construction

[0092] The present invention will be further described below in conjunction with accompanying drawing and embodiment:

[0093] Such as figure 1 As shown, a multi-model and multi-feature fusion wind speed prediction method along the high-speed railway includes the following steps:

[0094] Step 1: Install at least N auxiliary wind measuring stations around the position of the target wind measuring station, use the auxiliary wind measuring stations to collect the wind speed data of the auxiliary wind measuring stations in real time, and obtain the wind speed sample collection of the target wind measuring station and the auxiliary wind measuring stations;

[0095] Wherein, N is an integer greater than or equal to 5;

[0096] Step 2: Perform filtering and 1-layer depth wavelet decomposition on the data of the auxiliary wind measuring station and the data of the target wind measuring station in sequence, and extract the low-frequency data;

[0097] Step 3: Use low-frequency data ...

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Abstract

The invention discloses a multi-model and multi-feature fusion wind speed prediction method along a high-speed railway. The method comprises the following steps: 1. Installing 5 auxiliary wind measuring stations around the position of the wind measuring station; Multi-model Kalman filter method for processing; step 3: use the filtered data for wavelet processing, and construct a prediction sub-model for the low-frequency data after wavelet processing; step 4: advance the multi-step prediction model of the space-target wind station, The self-target anemometer multi-step forecast model and the weather-target anemometer multi-step forecast model get the multi-step forecast value of the target anemometer and the weather forecast wind speed forecast value of the target anemometer input into the Bayesian combination model , to obtain the final predicted value of the target wind measuring station; the invention can not only avoid the data interruption caused by the hardware failure of a single wind measuring station, but also provide longer emergency processing time for the safe driving of the high-speed railway under the severe wind environment.

Description

technical field [0001] The invention belongs to the field of railway wind speed prediction, in particular to a multi-model and multi-feature fusion method for wind speed prediction along a high-speed railway. Background technique [0002] With the sustained and stable development of my country's economy, my country's railway construction has entered a period of rapid development. With the increase of railway operating lines and the improvement of train speed, more and more attention has been paid to the safety, stability and comfort of train operation. Strong wind is one of the main natural disasters leading to train accidents. Strong winds often occur in some areas along the railways in my country, which brings great challenges to the safe and stable operation of trains. In order to prevent train accidents, it is necessary to establish a railway gale monitoring and early warning system so that the railway department can dispatch and command in advance. The wind speed predi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N99/00
CPCG06N3/006G06N3/04G06N3/08G06N3/084G06N20/00G06Q10/04G06Q50/30G06N3/044
Inventor 刘辉李燕飞
Owner CENT SOUTH UNIV
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