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

Two-dimensional code anti-counterfeiting prediction device and method based on bp neural network

A BP neural network and prediction device technology, applied in the field of two-dimensional code anti-counterfeiting prediction, to avoid misjudgment, meet the psychological needs of shopping, and predict the results accurately

Active Publication Date: 2018-04-17
GUANGDONG UNIV OF TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the application document CN201410464900.1, it is mentioned to use BP neural network to predict the time of task completion, but in the prior art, there is no device and method for using BP neural network to predict the authenticity of products. Therefore, based on BP Neural network, the method and device for judging the authenticity of products by scanning codes are yet to be developed

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
  • Two-dimensional code anti-counterfeiting prediction device and method based on bp neural network
  • Two-dimensional code anti-counterfeiting prediction device and method based on bp neural network
  • Two-dimensional code anti-counterfeiting prediction device and method based on bp neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0061] Such as figure 1 and 2 As shown, the present invention provides a two-dimensional code anti-counterfeiting prediction device based on BP neural network, including a data access module, a code scanning module, a data analysis module, a learning training module and an algorithm application module connected sequentially according to the signal flow direction; The BP neural network is composed of input layer, hidden layer and output layer.

[0062] Data access module, the data access module is used to store the enterprise's processed product quality information, dealer information, retailer information, consumer scan code verification information and packaging two-dimensional code information and establish an anti-counterfeiting database, through The anti-counterfeiting database is constantly updated and expanded in many ways, making the prediction of the probability of product counterfeiting more accurate. The enterprise processes the products, marks the qualified produc...

Embodiment 2

[0076] Such as image 3 As shown, the two-dimensional code anti-counterfeiting prediction method based on BP neural network of the present invention, the processing process includes four steps, and the specific implementation steps are as follows:

[0077] Step 1: Establish an existing anti-counterfeiting database; used to access product data in the anti-counterfeiting database; information such as enterprise processing product quality information, dealer information, retailer information, consumer scan code verification information and packaging QR codes are stored through the data The acquisition module is stored in the anti-counterfeiting database, and with the code scanning information, the data is converted into the product attribute characteristic value required for BP neural network training, which is conducive to the unified storage of data and convenient access to data.

[0078] Step 2: Scan to obtain product information; scan the QR code of the product through the sc...

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 BP neural network based two-dimensional code anti-counterfeiting prediction apparatus and method. The apparatus comprises the following elements connected in succession based on the flow direction of signals: a data accessing module for accessing the product data to establish an anti-counterfeiting database, a scanning module for acquiring the data by scanning, a data analyzing module for calling the anti-counterfeiting database to process and analyze the data acquired by scanning and for obtaining the attribute characteristic constant of the product, a learning training module to establish a BP neural network algorithm, and an algorithm application module for using the BP neural network algorithm to conduct anti-counterfeiting prediction to the scanned product. With the method, a consumer firstly scans the two-dimensional code to determine whether the product is a real one or not before he or she decides to purchase it. In this way, the defect can be overcome that a consumer must purchase the product first before scanning the product.

Description

technical field [0001] The invention relates to the technical field of two-dimensional code anti-counterfeiting prediction, in particular to a two-dimensional code anti-counterfeiting prediction device and method based on BP neural network. Background technique [0002] With the improvement of social living standards, people have higher and higher requirements for product quality, and the demand for anti-counterfeiting technology applications has also increased accordingly. The anti-counterfeiting system based on the QR code is currently widely used at home and abroad. The product is bound to the QR code, and the QR code is scanned with a smartphone to prompt the authenticity of the product. At the same time, with the popularity of smart phones, it will be easier for the public to participate in product anti-counterfeiting, and the application of two-dimensional code anti-counterfeiting systems will become more and more extensive. For the current two-dimensional code anti-c...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/08
CPCG06N3/084G06Q10/04G06Q30/0185
Inventor 李志陈光锋
Owner GUANGDONG UNIV OF TECH
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