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Method and system for judging disaster risk level based on rain condition data

A technology of risk level and disaster, applied in the high-level field, can solve the problems of high deployment hardware environment requirements, poor scalability, and high upgrade costs, and achieve the effect of enhancing discovery capabilities, improving efficiency, and high accuracy

Active Publication Date: 2022-04-26
北京慧图科技(集团)股份有限公司
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Problems solved by technology

[0005] In view of the above analysis, the embodiment of the present invention aims to provide a method for judging the disaster risk level based on rain data, so as to solve the problem that the existing rain data that has been collected and / or predicted rainfall data cannot be effectively used to determine the level of disaster wind direction in the future. And trends are predicted, and the requirements for the deployment hardware environment are high, the upgrade cost is high, and the scalability is poor

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  • Method and system for judging disaster risk level based on rain condition data
  • Method and system for judging disaster risk level based on rain condition data
  • Method and system for judging disaster risk level based on rain condition data

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Embodiment Construction

[0049] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and together with the embodiments of the present invention are used to explain the principle of the present invention and are not intended to limit the scope of the present invention.

[0050] Such as figure 1 As shown, the artificial intelligence technology adopted in the present invention is based on the data analysis technology of DNN (deep neural network), is based on traditional ANN (artificial neural network), through deep learning mode, has merged CNN (convolutional neural network) Network), RNN (recurrent neural network and recurrent neural network) and other neural network models form a more accurate and effective data analysis method. The model converts sequence data into more complex digital matrix data. The neural network system is used in the recognition system...

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Abstract

The invention relates to a method and system for judging a disaster risk level based on rain condition data, belongs to the technical field of artificial intelligence data analysis, and solves the problem that the wind direction level and trend of a future disaster cannot be effectively predicted in the prior art. The method comprises the following steps: acquiring rainfall data of each station, and constructing a rainfall accumulation histogram of each station according to a time sequence; inputting the rainfall accumulation histogram into a corresponding current optimal disaster risk level prediction model, and obtaining disaster prediction risk level information corresponding to a prediction moment and corresponding probability information; acquiring actual risk level information at a prediction moment; and when the disaster prediction risk level information corresponding to the prediction moment is different from the actual risk level information, training the disaster risk level prediction model of the site by using the rainfall accumulation histogram marked by the actual risk level of the site, and updating the current optimal disaster risk level prediction model of the site.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence data analysis, in particular to a method and system for judging disaster risk levels based on rain data. Background technique [0002] In recent years, with global warming, the meteorological environment has become more complex and diverse, and disastrous weather is showing an increasing trend. Improving disaster prevention and mitigation capabilities, reducing losses caused by disasters, and promoting safe and sustainable development of society have become the top priorities. heavy. Strengthen the effective monitoring of natural disasters by artificial intelligence, and build an intelligent monitoring, early warning and comprehensive response platform around major natural disasters such as earthquake disasters, geological disasters, meteorological disasters, floods and droughts, and marine disasters. Judging from the trend, intelligence will be the next commanding height of infor...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/26G06K9/62G06N3/08G06Q10/04
CPCG06Q10/0635G06Q10/04G06Q50/26G06N3/084G06F18/2415Y02A90/10
Inventor 夏述海姚毅霍宏旭
Owner 北京慧图科技(集团)股份有限公司
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