Method and device for food risk traceability information classification, and computer readable storage medium

US11568230B2 · kind B2 · utility

Assignees

• SHENZHEN ACADEMY OF INSPECTION AND QUARANTINE · CN
• SHENZHEN CUSTOMS INFORMATION CENTER · CN
• SHENZHEN CUSTOMS ANIMAL AND PLANT INSPECTION AND QUARATINE TECHNOLOGY CENTER · CN

Inventors

• Yina Cai · Lo Wu, CN
• Xianyu Bao · Lo Wu, CN
• Zhouxi Ruan · Lo Wu, CN
• Wenli Zheng · Yundonghai, CN
• Heping Li · Guiyang, CN
• Tikang Lu · Lo Wu, CN
• Zhinan Chen · Lo Wu, CN

Key dates

• Filing date: Sep 2, 2020
• Grant date: Jan 31, 2023
• Expiry date: Jun 23, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/047
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

The present disclosure provides a method, a device and a computer readable storage medium for food risk traceability information classification. The method includes: building a deep learning neural networks model by a self-learning ability of an artificial intelligence model, initializing weights and a bias of the built model, and obtaining an original deep learning neural networks model; obtaining samples of food risk traceability information, dividing the samples, and obtaining factors of the food risk traceability information, converting the factors into vectors of the food risk traceability information; inputting the vectors into the original deep learning neural networks model, and obtaining original classification vectors of current food risk traceability information; and inputting the original classification vectors into a loss function, obtaining a loss rate of the original classification vectors, and determining the original classification vectors as a target classification result in response to the loss rate being within a preset range.