Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Wine quality discriminating method based on reABC-SVM

A quality identification and wine technology, applied in the field of wine quality classification based on reABC-SVM, can solve problems such as identification

Inactive Publication Date: 2017-09-08
ANHUI UNIVERSITY
View PDF0 Cites 3 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the deficiencies of the prior art, the present invention provides a wine quality identification method based on reABC-SVM, in order to optimize the SVM parameters by using the improved ABC algorithm, so as to obtain the most suitable classification model to realize the wine quality identification method. Classification, and then solve the problem of wine quality identification

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wine quality discriminating method based on reABC-SVM
  • Wine quality discriminating method based on reABC-SVM
  • Wine quality discriminating method based on reABC-SVM

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0044] In this example, if figure 1 As shown, a wine quality identification method based on reABC-SVM aims to apply the improved artificial bee colony support vector machine method to wine quality identification. Specifically, it proceeds as follows:

[0045] Step 1: Obtain the feature vector set of N wines to form a training sample set, denoted as V=[V 1 ,V 2 ,...,V i ,...,V N ], where V i is the eigenvector of the ith wine, and has is the jth eigenvalue of the ith wine, y i is the quality of the ith wine, and y i = 1 means the quality of the i-th wine is excellent, y i = 0 means the quality of the i-th wine is inferior; 1≤i≤N, 1≤j≤n;

[0046] Step 2: based on the training sample set V, use the improved artificial bee colony optimization algorithm to dynamically adjust the penalty coefficient C of the support vector machine and the parameter g of the RBF kernel function, thereby establishing an optimal classification model for wine quality identification;

[0047]...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a wine quality discriminating method based on reABC-SVM. The method comprises the steps of 1, extracting a sample from the wine, and measuring contents of certain materials in a wine sample for forming a training sample set; and 2, performing dynamic adjustment on a penalty factor and a nuclear function parameter of a support vector machine by means of an improved artificial bee colony optimization algorithm, outputting an optimal parameter, and establishing a wine discriminating model by means of an optimal parameter, thereby realizing quality discriminating on the wine. According to the wine quality discriminating method, an SVM parameter can be optimized by means of an improved ABC algorithm, thereby obtaining a most appropriate classification model for realizing wine quality classification, and furthermore settling a wine quality discriminating problem.

Description

technical field [0001] The invention designs the field of wine quality identification, specifically a wine quality classification method based on reABC-SVM. [0002] technical background [0003] Wine is rich in nutrients, and up to now more than 600 kinds of substances have been determined. The nutritional and medical effects of grapes have been known for a long time, and wine is becoming more and more popular among consumers because of its special nutritional value and good health effects. So how to accurately identify the quality of wine is particularly important. For the traditional wine identification method, it usually depends on the subjective evaluation of wine judges. This evaluation method is not universal at first, and absolutely depends on wine judges. Second, after the workload is greatly increased, the accuracy of the tasters' bottle wines may be greatly inaccurate, which may have disastrous consequences. So more precise identification tools are needed. [0...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/2411
Inventor 程凡张雪锋王劲松邱剑锋尹凯黄少聪
Owner ANHUI UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com