AI can enhance screening and detecting the non-compliance food foreign facilities

다국어 초록 (Multilingual Abstract)

Free Trade Agreement has increased the global food trade at tremendous rate every year. With the annual trade in food growing exponentially, imported food controls need to be strengthened to protect consumer health and ensure fair trade. This study employee a supervised learning prediction model to detect nonconformity in advance of processed food manufacturing and processing businesses. The study was conducted according to the standard procedure of machine learning, such as definition of objective function, data preprocessing and feature engineering and model selection and evaluation. After applying the feature extraction methods, the machine learning algorithm was applied to data by deriving the company’s risk, item risk, environmental risk, and past violation history as feature variables. Based on the results of this study, it is expected that the official food control for food safety management will be enhanced and geared into the data-evidence based management as well as scientific administrative system.

목차 (Table of Contents)

• Abstract
• Introduction
• Method
• Results
• Conclusion
• References