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Grain quality index prediction method based on SVM support vector machine model

A technology of support vector machine and prediction method, which is applied in the direction of prediction, computer parts, character and pattern recognition, etc., and can solve the problems of wasting manpower and material resources and reducing efficiency

Pending Publication Date: 2019-11-15
CHINA GRAIN RESERVES CORP CHENGDU GRAIN STORAGE SCI INST
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Problems solved by technology

[0002] As we all know, ensuring the safety of my country's grain reserves is a major issue related to the national economy and the people's livelihood, and how to predict the changes in the quality of stored grains is of great significance for evaluating the quality of grain storage. In the prior art, most of the research on grain quality indicators is based on The method of experimental extraction, but because the initial level of grain in each ecological zone and each warehouse is different, if the grain quality indicators of each ecological zone and each warehouse are obtained by experimental extraction, the efficiency will be greatly reduced and manpower will be wasted material resources

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  • Grain quality index prediction method based on SVM support vector machine model
  • Grain quality index prediction method based on SVM support vector machine model
  • Grain quality index prediction method based on SVM support vector machine model

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Embodiment 1

[0042] Such as figure 1 As shown, the present embodiment provides a grain quality index prediction method based on the SVM support vector machine model, including:

[0043] S1: Select a part of grain in period t as sample grain;

[0044] S2: Measure the quality index data and quality index data of the sample grain as sample data {(x i，t ,y i，t )|i=1, 2,..., k}, where, x i is the quality index data, y i，t for and x i，t The corresponding quality index data, k is the amount of sample data;

[0045] S3: constructing an SVM support vector machine model according to the sample data;

[0046] S4: Measure the quality index data of the grain in period t, and predict the quality index of grain in period t according to the constructed SVM support vector machine model.

[0047] In this embodiment, the grain can be corn, wheat, japonica rice, indica rice, etc., and the index of grain includes quality index and quality index, wherein, the quality index of corn is the fatty acid value...

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Abstract

The invention discloses a grain quality index prediction method based on an SVM (Support Vector Machine) model. The method comprises the following steps: selecting a part of tth-stage grains as samplegrains; measuring quality index data of the sample grains and taking the quality index data as sample data; constructing an SVM support vector machine model according to the sample data; and measuring the quality index data of the t-th period of grain, and predicting the quality index of the t-th period of grain according to the constructed SVM support vector machine model. The corresponding quality index data of the grains in the same period can be predicted according to the SVM support vector machine model, the measurement workload can be reduced in the whole process, the efficiency is high, and manpower and material resources are saved.

Description

technical field [0001] The invention relates to the field of grain storage, in particular to a grain quality index prediction method based on an SVM support vector machine model. Background technique [0002] As we all know, ensuring the safety of my country's grain reserves is a major issue related to the national economy and the people's livelihood, and how to predict the changes in the quality of stored grains is of great significance for evaluating the quality of grain storage. In the prior art, most of the research on grain quality indicators is based on The method of experimental extraction, but because the initial level of grain in each ecological zone and each warehouse is different, if the grain quality indicators of each ecological zone and each warehouse are obtained by experimental extraction, the efficiency will be greatly reduced and manpower will be wasted physical resources. Contents of the invention [0003] In order to overcome the deficiencies in the prio...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26G06K9/62
CPCG06Q10/04G06Q10/06393G06Q50/26G06F18/2411
Inventor 陈晋莹邹潇陈猛
Owner CHINA GRAIN RESERVES CORP CHENGDU GRAIN STORAGE SCI INST
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