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Tea aroma classification method of parameter optimized support vector machine

A technology of support vector machine and classification method, which is applied in the field of tea aroma classification of parameter optimization support vector machine, can solve the problem of low accuracy, achieve the effect of improving efficiency and accuracy, improving classification accuracy, and ensuring fresh and tender taste

Inactive Publication Date: 2017-01-04
ANHUI AGRICULTURAL UNIVERSITY
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Problems solved by technology

[0004] On the issue of tea odor classification, there have been typical discriminant analysis methods and neural network methods, etc., but in the face of a large amount of tea aroma data, these algorithms have the problem of low accuracy. This patent aims at this problem. The algorithm optimizes the SVM parameter method to classify the aroma of tea to different degrees and improve the accuracy of classification

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  • Tea aroma classification method of parameter optimized support vector machine
  • Tea aroma classification method of parameter optimized support vector machine
  • Tea aroma classification method of parameter optimized support vector machine

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Embodiment 1

[0022] The present invention will be described in further detail below according to the accompanying drawings and embodiments, taking Maofeng tea as an example.

[0023] Step 1: Determine the detection index of Maofeng tea;

[0024] The preparation of step 1.1 Maofeng tea sample;

[0025] Prepare 70 repeated samples of Maofeng tea leaves of various grades, each repeated sample has a mass of 5g, sealed in a 500ml beaker with a double-layer film, and allowed to stand at room temperature for 45min.

[0026] According to the requirements of sensory evaluation, the ratio of tea to water is 1:50, and 5g of tea leaves are brewed with 250ml of water. The water for making tea is pure water boiling at a moderate temperature of 100°C, the brewing time is 5 minutes, and then the tea is filtered out. Seal the tea water and the tea base in a 500ml beaker respectively, and let it stand for 45 minutes so that the headspace of the beaker is enriched with the volatile components of the tea le...

Embodiment 2

[0093] Use the grid search algorithm to optimize the support vector machine, hereinafter referred to as GridSearch-SVM, and obtain the optimal penalty factor C and kernel function parameter g. Replace step 4 and step 5 in embodiment 1 with the following technical solutions:

[0094] Step 4: Use the grid search algorithm to optimize the support vector machine, perform model training, and output the best penalty factor C and kernel function parameter g;

[0095] Step 4.1 model training;

[0096] In this embodiment, the grid search algorithm is used to optimize the support vector machine to classify the aroma quality of Maofeng tea. For the support vector machine of the present invention, the parameter groups to be searched are the penalty factor C and the kernel function parameter g. Therefore, these two parameters can be divided into a grid in two-dimensional space and the optimal parameter group can be found through traversal testing. First, give the search range of these t...

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Abstract

The invention relates to a tea aroma classification method of a parameter optimized support vector machine, which aims to solve a problem of tea aroma classification through an improved support vector machine, and belongs to the field of tea aroma classification. The principle is that functions and characteristics of human sensory evaluation are simulated by using an electronic nose sensor, characteristic values of different sensors at different time are acquired, and a data set is established. The support vector machine is optimized by using an algorithm, an optimized penalty factor C and a kernel function parameter g are acquired, and thus a support vector machine (SVM) classification model of Maofening tea aroma is built. The beneficial effects lie in that the efficiency and the accuracy of predicted tea aroma classification can be improved, and an effective method for tea aroma classification is provided for consumers.

Description

technical field [0001] The invention relates to a tea aroma classification method, in particular to a tea aroma classification method using a parameter optimization support vector machine. Background technique [0002] Odor is an important indicator of food quality evaluation. At present, the evaluation of food odor mainly depends on experienced professionals. The evaluation is mainly done by combining sensory quantitative description analysis method, principal component analysis method and traditional scoring method. It is difficult for different people to get consistent evaluation results for the same smell; even the same person has different feelings and evaluations for the same smell in different environments and different emotions. As a result, there are certain limitations in using human senses to judge. In order to reduce the error rate of judgment, machines are used to simulate human senses (such as electronic eyes that simulate human vision, electronic tongues that...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/12
CPCG06N3/126G06F18/2411
Inventor 杨宝华钱彬彬戴前颖谢申汝徐光祥王淑娟杨玉洁
Owner ANHUI AGRICULTURAL UNIVERSITY
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