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Mountain torrent risk prediction method and prediction system

A risk prediction and torrent technology, applied in prediction, neural learning method, biological neural network model, etc., can solve the problems of torrent data prediction value error, difficult model migration, low model flexibility and historical data accuracy, etc. The effect of improving accuracy

Pending Publication Date: 2021-06-15
四川水利职业技术学院
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  • Abstract
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  • Application Information

AI Technical Summary

Problems solved by technology

This type of model is highly targeted and supported by historical data, but it has problems such as low flexibility of the model and accuracy of historical data. Therefore, the prediction value of flash flood data has a large error. Therefore, there is a problem that the model transfer is difficult

Method used

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  • Mountain torrent risk prediction method and prediction system
  • Mountain torrent risk prediction method and prediction system
  • Mountain torrent risk prediction method and prediction system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] This embodiment discloses a flash flood risk prediction method, such as figure 1 shown, including the following steps:

[0046] S1: Obtain the first data, the first data is the historically collected flash flood influencing factor data in the target area; the influencing factor data includes real-time collected real-time rainfall, real-time wind force, real-time wind direction, real-time air humidity, real-time slope, real-time temperature , real-time soil moisture and other data.

[0047] The cause of mountain torrents is closely related to rainfall. With the continuous increase of rainfall, the soil moisture with different infiltration rates is gradually saturated, reaching the critical rainfall of flash floods. According to different geological terrains, the formation time of mountain torrents will be different . According to the area of ​​the basin, there is a certain time difference between the rainfall and the final confluence into flash floods. Therefore, it ca...

Embodiment 2

[0077] This embodiment discloses a flash flood risk prediction system, such as figure 2 As shown, the risk prediction system can realize the risk prediction method as in Embodiment 1, and the prediction system includes:

[0078] The sensor module is used to acquire the first data, and the first data is the real-time collected mountain torrent influencing factor data. The sensor modules are different sensors, and different sensors are used to collect different mountain torrent impact data, and transmit the collected real-time data In the data processing module, it is stored and processed, and the parameters in the neural network model can be continuously optimized and diagnosed by accumulating a large amount of data transmitted by the sensor;

[0079] The data processing module is used to clean the first data and obtain the second data. The data processing module is mainly to process the data collected by the sensor. It is necessary to normalize or unify the data collected by ...

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Abstract

The invention discloses a mountain torrent risk prediction method and prediction system, and the method comprises the steps of obtaining first data, carrying out the data cleaning of the first data, and obtaining second data; dividing the second data into a training data set and a test data set, constructing a neural network model, inputting the training data set into the neural network model, and training the neural network model by adopting a loss function to obtain a training model; inputting the test data set into the training model to obtain an optimal model, inputting mountain torrent influence factor data obtained next time into the mountain torrent prediction risk model to obtain a mountain torrent value to be predicted, comparing the mountain torrent value to be predicted with a preset threshold value, if the mountain torrent value to be predicted is greater than the preset threshold value, determining that the target area has a mountain torrent outbreak risk, otherwise, determining that the target area has no mountain flood outbreak risk. The invention has the beneficial effects that the sensor module is arranged to collect various different real-time data, so that the accuracy of regional mountain torrent prediction is improved; and early warning can be provided for the user in real time.

Description

technical field [0001] The invention relates to the technical field of mountain torrent risk prediction, in particular to a method and system for predicting mountain torrent risk. Background technique [0002] Flash flood disasters are one of the most harmful natural disasters in the world. Flash flood disasters are characterized by strong suddenness, great destructive power, and unpredictability, and are likely to cause a large number of casualties, serious property damage, and environmental disasters. The defense of mountain torrent disasters is the focus and difficulty of our country's flood prevention and disaster reduction work. The timely and accurate early warning and forecasting of mountain torrent disasters is conducive to guiding the rapid evacuation of the affected people, reducing disaster losses, and ensuring the safety of people's lives and property. It is currently the most effective and feasible non-engineering measure for disaster prevention and mitigation. ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/04G06N3/08
CPCG06Q10/04G06N3/04G06N3/084Y02A10/40
Inventor 刘明锦张智涌王宾陈万林高瑞洁高键
Owner 四川水利职业技术学院