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Grain storage quality prediction method and device

A storage quality and prediction method technology, applied in the field of grain storage quality prediction, can solve problems such as low accuracy of grain storage quality prediction, and achieve the effect of accelerating the convergence speed and improving the accuracy

Pending Publication Date: 2021-01-05
HENAN UNIVERSITY OF TECHNOLOGY
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a grain storage quality prediction method and device to solve the problem of low accuracy of grain storage quality prediction

Method used

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  • Grain storage quality prediction method and device
  • Grain storage quality prediction method and device
  • Grain storage quality prediction method and device

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Embodiment Construction

[0040] The specific implementation manners of the present invention will be further described below in conjunction with the accompanying drawings.

[0041] method embodiment

[0042] The grain quality prediction method of the present invention is based on the neural network optimized by the improved PSO algorithm as the prediction method, wherein the main improvement of the PSO algorithm is to use a nonlinear function to update the inertia weight and learning factor in the PSO algorithm. The implementation process of this method will be described in detail below taking the study of wheat storage quality as an example.

[0043] 1. Build a predictive model.

[0044] The predictive model in the present embodiment adopts BP neural network, such as figure 1 As shown, BP neural network includes input layer, hidden layer and output layer, where x 1 ,...,x i ,...,x n is the input of BP neural network; w ji is the weight between input layer node i and hidden layer node j; w kj is ...

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Abstract

The invention relates to a grain storage quality prediction method and a device, and belongs to the technical field of grain quality prediction. According to the method, the inertia weight and the learning factor in the PSO algorithm are dynamically adjusted by adopting the nonlinear function, so that the PSO algorithm can be prevented from falling into a local extreme value, the weight and the threshold parameter in the neural network are updated by utilizing the improved PSO algorithm, the convergence rate of the BP neural network is increased, and the accuracy of the neural network as a prediction model is improved; and the related index data of the to-be-predicted grain storage is input into the prediction model to realize prediction of the grain storage quality. Therefore, the defectsthat a BP neural network and a PSO algorithm in grain storage quality prediction are prone to falling into a local extreme value, low in convergence speed and the like are effectively overcome, certain stability is achieved, and the accuracy of grain storage quality prediction is greatly improved.

Description

technical field [0001] The invention relates to a grain storage quality prediction method and device, belonging to the technical field of grain quality prediction. Background technique [0002] During the storage process of wheat, its quality will gradually change qualitatively or even deteriorate as the environment changes and the storage time prolongs, which reduces the edible quality and processing value of wheat, and causes a lot of economic losses. Quality change to reduce its loss is of great significance to the national economy. The existing literature shows that the physiological and biochemical indicators of wheat itself also change to a certain extent when qualitative changes occur, and its quality can be predicted by using this characteristic. At present, the changes in the quality of stored wheat are mainly detected by instruments and equipment, but this method has high labor and time costs, and ignores the interaction between various physiological and biochemic...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q10/08G06Q50/04G06N3/00G06N3/04G06N3/08
CPCG06Q10/04G06Q10/06393G06Q10/087G06Q50/04G06N3/006G06N3/084G06N3/045Y02P90/30
Inventor 蒋华伟郭陶杨震
Owner HENAN UNIVERSITY OF TECHNOLOGY