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A regional rainfall prediction method combining spatial reasoning and machine learning

A spatial reasoning and machine learning technology, applied in the field of spatial reasoning and machine learning, can solve problems such as difficult weather forecast decision-making, low level, complex rainfall forecast model equations, etc., and achieve the effect of improving the accuracy of rainfall forecasting and improving real-time performance

Active Publication Date: 2022-07-15
JILIN AGRICULTURAL UNIV
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  • Application Information

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Problems solved by technology

However, the formation and changes of the weather system interact with the geographical environment and atmospheric movement, so weather forecast decision-making is difficult and the level is low, and the existing rainfall forecast model equations are very complicated

Method used

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  • A regional rainfall prediction method combining spatial reasoning and machine learning
  • A regional rainfall prediction method combining spatial reasoning and machine learning
  • A regional rainfall prediction method combining spatial reasoning and machine learning

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Embodiment 1

[0053] A regional rainfall prediction method based on spatial reasoning and machine learning, which uses the methods and theories of spatial reasoning to describe the spatial location and climate state information of the area to be monitored, and then analyzes and analyzes it with the help of a deep neural network model in machine learning. Rainfall forecast; specific implementation steps are as follows figure 1 It includes the following 6 steps: observation data collection, observation data preprocessing, observation data preprocessing feature fusion, observation data feature extraction, observation data feature vector time series fusion, and rainfall prediction;

[0054] Wherein, step 1: observation data collection, using n radiosondes distributed in fixed positions to detect the state of the atmosphere as observation data; the observation data includes temperature value, humidity, whether it rains, and wind speed and direction;

[0055] Step 2: Preprocessing of observation ...

Embodiment 2

[0089] A training method for a regional rainfall prediction model based on spatial reasoning and machine learning, which includes preparing a training data set, pre-training and full network training;

[0090] Obtain the historical value of observation data of the state of the atmosphere detected by n radiosondes for a long time, and record the corresponding rainfall state;

[0091] For each observation data, according to the method in Example 1, generate a spatial relationship matrix, a wind speed matrix and a wind direction matrix, a temperature vector and a humidity vector, and according to the rainfall status of each simple area, according to the intersection matrix representation method, generate its label rainfall Matrix, the dimension is n+2 in width and height;

[0092] The above-mentioned spatial relationship matrix, wind speed matrix and wind direction matrix, temperature vector, humidity vector and label rainfall matrix are a set of training data;

[0093] The hist...

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Abstract

A regional rainfall prediction method combining spatial reasoning and machine learning, using the methods and theories of spatial reasoning to describe the spatial location and climate state information of the area to be monitored; and then analyze it with the help of a deep neural network model in machine learning The specific implementation steps are: observation data collection, observation data preprocessing, observation data preprocessing feature fusion, observation data feature extraction, observation data feature vector time series fusion, and rainfall prediction. The complexity of the rainfall prediction model ensures the real-time performance of its application.

Description

technical field [0001] The invention relates to spatial reasoning and machine learning, in particular to a regional rainfall prediction method based on spatial reasoning and machine learning. Background technique [0002] With the development of today's society, the impact of meteorological changes on people's social life and production cannot be ignored, and people's requirements for the real-time and accuracy of meteorological forecasting are getting higher and higher, especially rainfall forecasting. However, the formation and changes of the weather system interact with the geographical environment and atmospheric movement, so the decision-making of weather forecast is difficult and the level is low. The existing rainfall prediction model equations are very complicated. SUMMARY OF THE INVENTION [0003] The purpose of the present invention is to provide a regional rainfall prediction method based on spatial reasoning and machine learning, which is used for rapid and acc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/26G06N3/04
CPCG06Q10/04G06Q50/26
Inventor 李健刘孔宇于合龙熊琦胡雅婷汪威王国伟温长吉常晶周晶任虹宾
Owner JILIN AGRICULTURAL UNIV
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