Lightning intensity value predicting method based on atmospheric electric field data

A technology of atmospheric electric field and prediction method, which is applied in the fields of atmospheric potential difference measurement, weather condition prediction, meteorology, etc., can solve the problems of inability to obtain thunderstorm intensity information, few prediction methods, and thunderstorm intensity value prediction, etc., to achieve enhanced atmospheric electric field The effect of data structure expression

Active Publication Date: 2018-02-23
BEIJING UNIV OF TECH
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Problems solved by technology

This method only uses atmospheric electric field data to predict the frequency of thunderstorms, but does not predict the intensity of thunderstorms, that is, it lacks the prediction of thunderstorm parameters and cannot obtain the intensity information when thunderstorm

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  • Lightning intensity value predicting method based on atmospheric electric field data
  • Lightning intensity value predicting method based on atmospheric electric field data
  • Lightning intensity value predicting method based on atmospheric electric field data

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Embodiment Construction

[0054] The present invention combines atmospheric electric field data with lightning data to provide a depth feature of a two-dimensional transformation map based on atmospheric electric field data. Prediction of intensity values. The realization steps of this invention are as follows:

[0055] This method is based on the depth characteristics of the atmospheric electric field data. First, the original one-dimensional atmospheric electric field data is converted into a two-dimensional image, and then the depth feature information of the atmospheric image is extracted through a deep learning model, and then the thunderstorm intensity value of the lightning locator is maximized. After sampling, combined with the nonlinear regression analysis method, the relationship model between the atmospheric electric field data and the lightning intensity value is established, and the method of using the atmospheric electric field data to predict the lightning intensity value is realized.

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Abstract

The invention discloses a lightning intensity value predicting method based on atmospheric electric field data, which is applied to the field of lightning early warning. The disclosed lightning intensity value predicting method is used for converting original one-dimensional atmospheric electric field data into a two-dimensional image representation through extracting depth features of the atmospheric electric field data, mining depth feature information of the image, establishing a relationship model of the atmospheric electric field data and a lightning intensity value by combining with a non-linear regression analysis method, and predicting the lightning intensity value. According to the lightning intensity value predicting method, various kinds of detection data is used for performinglightning early warning, i.e., the atmospheric electric field data and lightning data; the one-dimensional atmospheric electric field data is converted into the two-dimensional image representation byadopting a dimension conversion method, so as to enhance the structure representation of the atmospheric electric field data; the depth feature information of the atmospheric electric field data is extracted by using a depth model; and the lightning intensity value is predicted by using the atmospheric electric field data, thereby filling a gap of low utilization of the atmospheric electric fielddata in other predicting methods and a gap of lightning intensity value prediction.

Description

technical field [0001] The invention is applied to the field of lightning early warning and relates to the application of atmospheric electric field data and lightning intensity values. The present invention proposes a method of extracting the depth characteristics of atmospheric electric field data, converting the original one-dimensional atmospheric electric field data into two-dimensional image expression and mining the depth feature information of the image, and combining the nonlinear regression analysis method to establish atmospheric electric field data and lightning intensity The relational model of the value is used to predict the value of lightning intensity. Background technique [0002] Thunderstorms are common convective weather accompanied by lightning, thunder, high winds, hail, and heavy precipitation. The lightning strike process has the characteristics of transient large current, high voltage, and strong electromagnetic radiation. The destructive force pr...

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Application Information

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IPC IPC(8): G01W1/10G01W1/16
CPCG01W1/10G01W1/16
Inventor 毋立芳郭橙杜建苹包坤李庆申
Owner BEIJING UNIV OF TECH
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