Deep-learning-based weather forecasting method and system

A technology of deep learning and weather prediction, applied in neural learning methods, forecasting, knowledge expression, etc.

Inactive Publication Date: 2017-09-15
台州市吉吉知识产权运营有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is to provide a weather forecasting method and system based o

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  • Deep-learning-based weather forecasting method and system
  • Deep-learning-based weather forecasting method and system
  • Deep-learning-based weather forecasting method and system

Examples

Experimental program
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Embodiment 1

[0044] This embodiment provides a weather prediction method based on deep learning, such as figure 1 shown, including steps:

[0045] S11: save the collected historical weather data and real-time weather data;

[0046] S12: Establish a layer-by-layer deep learning model according to the weather data and continuously correct the deep learning model;

[0047] S13: synchronizing the collected real-time weather data into the deep learning model;

[0048] S14: Obtain an output result according to the deep learning model after importing the real-time weather data.

[0049] Prior knowledge about meteorology is a very important part of weather forecasting, and it is the core of previous expert systems, which is related to the quality of the forecasting effect. And this kind of knowledge is mostly empirical knowledge, which is obtained through continuous learning and exploration by meteorologists. Finding laws and methods in massive data is one aspect that deep learning is good at,...

Embodiment 2

[0100] This embodiment provides a weather prediction method based on deep learning, such as figure 2 shown, including steps:

[0101] S21: save the collected historical weather data and real-time weather data;

[0102] S22: Constructing a deep learning model using a denoising autoencoder;

[0103] S23: Using support vector machine classification to adjust and correct the deep learning model;

[0104] S24: Synchronize the collected real-time weather data into the deep learning model;

[0105] S25: Obtain an output result according to the deep learning model after importing the real-time weather data.

[0106] The difference from the first embodiment is that in the first embodiment, step S12 specifically includes step S22 and step S23.

[0107] Pattern training is divided into two processes, which are bottom-up unsupervised learning and top-down supervised learning methods.

[0108] like Figure 4 As shown, since the present invention uses unprocessed original data for an...

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Abstract

The invention relates to a deep-learning-based weather forecasting method and system, so that a problem that weather forecasting is carried out by manual data screening based on priori knowledge in the prior art can be solved. The method comprises: S1, storing collected historical weather data and real-time weather data; S2, establishing a layer-by-layer deep learning model based on the weather data and continuously correcting the deep learning model; S3, synchronously collecting the real-time weather data into the deep learning model; and S4, obtaining an output result based on the deep learning model with the real-time weather data inputted. Therefore, data can be stored in different databases; output results of different needs are obtained by constructing different deep learning models; and a model with high prediction rate can be obtained by weather forecasting deep learning.

Description

technical field [0001] The present invention relates to the field of weather forecasting, in particular to a deep learning-based weather forecasting method and system. Background technique [0002] Weather forecasting is a very important part of our lives. A good forecasting system is not only beneficial to our travel, but also reduces the losses caused by natural disasters to the country and people. [0003] Usually, when forecasting weather conditions, forecasts can be made based on weather data collected by large-scale equipment such as satellites and radars, or based on weather data collected by professional collectors on the spot. [0004] The weather data collected by large-scale equipment such as satellites and radars is macro-scale weather data with a large granularity, which makes it impossible to accurately collect weather data in local areas, and the feedback of weather data from large-scale equipment is slow and time-sensitive, and cannot be real-time At the sam...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06F17/30G06N3/08G06N5/02
CPCG06F16/35G06N3/08G06N5/025G06Q10/04
Inventor 廖武
Owner 台州市吉吉知识产权运营有限公司
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