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Grain pile condensation prediction method based on support vector regression (SVR)

A support vector regression and prediction method technology, applied in the field of grain storage, can solve the problems of not being able to know the grain condensation, the specific location is difficult, and the moisture content requires a lot of manpower and material resources.

Pending Publication Date: 2021-06-08
HENAN UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] If condensation occurs inside the grain pile, its specific location is difficult to see with the naked eye, and the moisture must be checked regularly by taking samples. If the samples at the condensation part cannot be taken, it is impossible to know whether the condensation has occurred in the grain, and the moisture content of the grain sample The determination of content requires a lot of manpower and material resources

Method used

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  • Grain pile condensation prediction method based on support vector regression (SVR)
  • Grain pile condensation prediction method based on support vector regression (SVR)
  • Grain pile condensation prediction method based on support vector regression (SVR)

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Embodiment 1

[0035] refer to figure 1 As shown, the present invention proposes a method for predicting dew condensation in grain piles based on support vector regression SVR, which specifically includes the following steps:

[0036] 1. Feature extraction:

[0037] First of all, temperature and humidity sensors are arranged at different positions of the grain pile to regularly read the data factors affecting the humidity of the grain pile during the storage process; refer to figure 2 As shown in the figure, the black dots in the figure are the arrangement points of the temperature and humidity measuring sensors. The position and quantity of the arrangement points can be adjusted according to the position where the warehouse is prone to condensation and the size of the warehouse; Read and record temperature and humidity data. The data includes: grain temperature, grain moisture, and humidity in the grain pile at each position of the grain pile; then these data are preprocessed and classif...

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Abstract

The invention discloses a grain pile condensation prediction method based on support vector regression (SVR). The method specifically comprises the following steps: S1, extracting factors influencing the humidity of a grain pile as features; s2, performing data preprocessing on the features; s3, inputting the preprocessed features into an SVR model for optimization; and S4, utilizing the optimized SVR model to predict the local humidity and the dew formation condition of the grain pile. According to the invention, the prediction model which is robust to noise is constructed by utilizing the SVR, the humidity of different positions of the grain pile at different storage time can be predicted, and a new thought is provided for finding the local high-humidity position of the grain pile, judging whether the local part of the grain pile has dew formation or not, and taking measures such as ventilation and moisture dissipation.

Description

technical field [0001] The invention belongs to the technical field of grain storage, in particular to a grain pile dew condensation prediction method based on support vector regression SVR. Background technique [0002] Condensation in grain piles is caused by the microcirculation of the air in the pores of the grain piles due to the temperature difference in different positions of the grain piles. With the flow of air in the pores of the grain piles, when the hot air somewhere hits the cold grain, it will make The local humidity increases, and if the temperature difference is large, condensation will occur, which will lead to an increase in the local moisture of the grain pile, which will cause mildew and cause the loss of stored grain. When the seasons alternate, the temperature outside the warehouse and the upper space of the grain pile suddenly rises and falls suddenly. Since grain is a poor conductor of heat, there will be temperature differences between the surface an...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06K9/62G06N20/10G06F119/10
CPCG06F30/27G06N20/10G06F2119/10G06F18/2411
Inventor 渠琛玲靳小波孙辉王胜王若兰
Owner HENAN UNIVERSITY OF TECHNOLOGY
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