基于大数据的食品安全智能监管模型研究

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摘 要：针对食品安全大数据时代的监管需求，本研究构建了基于深度学习的全流程智能监管模型。该模型可实现监管数据自动采集、食品安全事件精确识别，并通过知识图谱进行智能风险判断，大大提高了食品安全监管效率。本研究首次实现了食品安全领域从采集到预警的自动化智能监管，为构建智能化监管体系提供了重要借鉴。

关键词：食品安全；大数据；智能监管；模型

Research on Intelligent Food Safety Supervision Model Based on Big Data

WANG Xuan， ZHANG Ailei*

（Tianjin Institute of Food Safety Testing Technology， Tianjin 300308， China）

Abstract： In response to the regulatory requirements in the era of big data for food safety， this study constructs an end-to-end intelligent regulatory model based on deep learning. The model achieves automatic collection of regulatory data， accurate identification of food safety incidents， and intelligent risk judgment through knowledge graphs， which greatly improves the efficiency of food safety regulation. This is the first study to realize automated intelligent regulation from collection to early warning in the field of food safety， thus providing important reference for building an intelligent regulatory system.

Keywords： food safety; big data; intelligent supervision; model

食品作為人类赖以生存的基本必需品，其安全关系到国计民生。（剩余6242字）

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