Method and system for automatic identification and tracking of low vortex and shear line based on deep learning
A deep learning and automatic identification technology, applied in the field of meteorology, can solve the problems of unable to replace the manual identification of meteorological workers, low accuracy, etc.
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[0126] The present invention will be described below with reference to specific examples. Those skilled in the art can understand that these examples are only for illustrating the present invention, and they do not limit the scope of the present invention in any way.
[0127] The automatic identification and tracking method of low eddy and shear lines based on deep learning includes the following steps:
[0128] S1. Collect, store and preprocess the reanalysis data and numerical model prediction results to obtain a normalized data set;
[0129] In this example, the reanalysis data and meteorological station data for the 30 years from 1990 to 2019 are prepared; such as figure 1 As shown, the implementation of step S1 includes the following steps:
[0130] S101. Automatically download historical, real-time reanalysis data and numerical model forecast results, and automatically store the meteorological element field by date,
[0131] S102. Perform data format conversion on the...
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