【摘要】 【目的】在大数据时代,粮食安全领域产生了海量多维数据,对这些数据进行关联分析、多维透视和知识挖掘,可以有效地支撑粮食安全分析与智能决策。【方法】基于粮食安全领域需求,系统地描述了粮食安全分析与智能决策系统的体系架构、数据基础、指标体系和预警模型。以"昆阅粮食安全大数据分析与智能决策系统"为例,展示了粮食安全结构分析、因素分析、平衡分析、图谱预警与智能决策等应用服务。【结果】该系统可为区域粮食安全评估、粮食安全预警等决策分析提供快速、精准、多角度、个性化的知识服务。【结论】多维数据驱动的粮食安全分析与智能决策系统具有巨大潜力,能够分析全国各地区每年粮食安全的状态,但还需集成人工智能领域中的新模型和新方法,以提升粮食安全分析与智能决策的效能。更多还原

【Abstract】 [Objective]In the era of big data,the field of food security has produced massive multidimensional data.These data are used for association analysis,multidimensional perspective,and knowledge mining,and can effectively support food security analysis and intelligent decision-making.[Methods]This paper systematically describes the system architecture,data schema,index system,and early warning model of food security analysis.Taking “Kunyue food security big data analysis system (KEDS)” as an example,this paper shows the services of food security structure analysis,factor analysis,balance analysis,security early warning and intelligent decision-making,etc.[Results]KEDS can provide fast,accurate,multi angle and personalized knowledge services for regional food security assessment,food security early warning and other decision-making analysis.[Conclusions]Multidimensional data driven food security analysis and intelligent decision-making system has great potential to analyze the state of food security in various regions every year,but it also needs to integrate new artificial intelligence models and methods to improve the efficiency and performance.更多还原