Progress in Food Security Risk Sensing and Early Warning Studies Incorporating Intelligent Algorithms

Abstract

Food security risk perception and early warning are of great significance to guarantee global food security. This paper provides a systematic review of the research in this field, covering core technologies such as multi-source data fusion and intelligent algorithms, analyzing the application and effectiveness of single Baidu intelligent algorithm and multi-algorithm fusion model, exploring the practice in the fields of food production prediction and quality and safety risk assessment, analyzing the existing challenges and looking forward to the future trends, so as to provide comprehensive and in-depth references for the related research. This study compiles a large amount of literature and combines practical cases and data analysis to help understand the mechanism, application potential and development direction of intelligent algorithms in food security risk perception and early warning.