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A rainstorm identification method and device based on multi-model fusion convolutional network

A technology of convolutional network and convolutional neural network, which is applied in the field of rainstorm recognition based on multi-model fusion convolutional network, can solve the problems of low recognition accuracy and achieve the effect of solving low recognition accuracy and improving accuracy

Active Publication Date: 2022-05-13
北京弘象科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of this, the object of the present invention is to provide a rainstorm identification method and device based on multi-model fusion convolutional network, to alleviate the technical problem of low identification accuracy of existing rainstorm identification methods

Method used

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  • A rainstorm identification method and device based on multi-model fusion convolutional network
  • A rainstorm identification method and device based on multi-model fusion convolutional network
  • A rainstorm identification method and device based on multi-model fusion convolutional network

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Embodiment 1

[0026] According to an embodiment of the present invention, an embodiment of a rainstorm recognition method based on a multi-model fusion convolutional network is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be implemented in a set of computer-executable instructions such as computer system, and although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.

[0027] figure 1 is a flow chart of a rainstorm identification method based on a multi-model fusion convolutional network according to an embodiment of the present invention, such as figure 1 As shown, the method includes the following steps:

[0028]Step S102, acquire the sample Doppler radar base data of the area to be identified, and determine the attribute information of the storm body contained in the sample Doppler radar base data based on the sample Dop...

Embodiment 2

[0090] The embodiment of the present invention also provides a rainstorm identification device based on a multi-model fusion convolutional network, which is used to implement the multi-model fusion convolutional network based on the above content provided by the embodiment of the present invention. The rainstorm identification method based on convolutional network, the following is a specific introduction of the rainstorm identification device based on multi-model fusion convolutional network provided by the embodiment of the present invention.

[0091] Such as image 3 as shown, image 3 It is a schematic diagram of the rainstorm recognition device based on the multi-model fusion convolutional network, which includes: an acquisition unit 10 , a construction unit 20 , a training unit 30 and a recognition unit 40 .

[0092] The acquiring unit 10 is configured to acquire sample Doppler radar base data of an area to be identified, and determine the attributes of storm bodies con...

Embodiment 3

[0098] An embodiment of the present invention also provides an electronic device, including a memory and a processor, the memory is used to store a program that supports the processor to execute the method described in the first embodiment above, and the processor is configured to execute the program stored in memory.

[0099] see Figure 4 , the embodiment of the present invention also provides an electronic device 100, including: a processor 50, a memory 51, a bus 52 and a communication interface 53, the processor 50, the communication interface 53 and the memory 51 are connected through the bus 52; Executable modules, such as computer programs, stored in the execution memory 51 .

[0100] Wherein, the memory 51 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory. The communication connection between the system network element and at least one other net...

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Abstract

The invention provides a rainstorm identification method and device based on a multi-model fusion convolutional network, which relates to the technical field of rainstorm early warning, including: acquiring sample Doppler radar base data of the area to be identified, and based on the sample Doppler radar base The data determine the attribute information of the storm body contained in the sample Doppler radar base data; obtain the observation data of the area to be identified sent by the ground observation station, and build a data set based on the observation data and attribute information; input the data set into the multi-model Fuse the convolutional network, train and optimize the multi-model fusion convolutional network, and obtain the rainstorm identification model; after obtaining the current Doppler radar base data in the area to be identified, use the current Doppler radar base data and the rainstorm identification model, Whether a rainstorm occurs in the area to be identified is determined, and the technical problem of low identification accuracy of the existing rainstorm identification method is solved.

Description

technical field [0001] The present invention relates to the technical field of rainstorm identification, in particular to a rainstorm identification method and device based on a multi-model fusion convolutional network. Background technique [0002] Heavy rain is one of the types of severe convective weather, which is a kind of bad weather. Its formation process is quite complicated. Generally speaking, from the perspective of macroscopic physical conditions, the main physical conditions for heavy rain are sufficient and continuous water vapor, strong and long-lasting upward movement of air currents, and instability of atmospheric structure. Heavy rains have different negative impacts on many industries. For example, heavy rains may damage soil and vegetation, affect people's normal travel, and be prone to floods and waterlogging. Therefore, the monitoring and early warning of bad weather such as heavy rain is very necessary. However, it is also one of the more difficult pr...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/764G06V10/774G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/25G06F18/24G06F18/214
Inventor 柴文涛钟科薛洪斌谭永强
Owner 北京弘象科技有限公司
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