| 多维数据驱动粮食供应链危害物风险综合评价 |
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| 引用本文： | 王小艺,王珍妮,孔建磊,金学波,苏婷立,张新.多维数据驱动粮食供应链危害物风险综合评价[J].北京工商大学学报(自然科学版),2019,37(6):129-138. |
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| 作者姓名： | 王小艺 王珍妮 孔建磊 金学波 苏婷立 张新 |
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| 作者单位： | 北京工商大学 计算机与信息工程学院, 北京 100048;北京工商大学 北京市食品安全大数据技术重点实验室, 北京 100048,北京工商大学 计算机与信息工程学院, 北京 100048,北京工商大学 计算机与信息工程学院, 北京 100048;北京工商大学 北京市食品安全大数据技术重点实验室, 北京 100048,北京工商大学 计算机与信息工程学院, 北京 100048;北京工商大学 北京市食品安全大数据技术重点实验室, 北京 100048,北京工商大学 计算机与信息工程学院, 北京 100048,北京工商大学 计算机与信息工程学院, 北京 100048 |
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| 摘 要： | 为科学合理评价重金属、真菌毒素、农药残留和微生物等危害物在粮食供应链各个环节中的综合风险,在分析全国26个省份粮食加工品抽检数据及其他多维度数据基础上,兼顾定量指标和定性指标优势,从统计特性、抽检特性和调研特性三种互补角度构建多维层次风险指标体系,实现大量异构数据向量化风险指标转变；继而应用关联规则挖掘各指标间内在关系,实现各指标权重分配,构建风险综合评价方法,实现多维数据驱动的粮食供应链危害物风险评价和优先程度排序。希望为监管部门制定有针对性的抽检策略、确立优先监管领域和分配风险监管资源提供科学依据。
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| 关 键 词： | 粮食危害物 供应链安全 多维层次指标 关联规则挖掘 风险评价 多源异构数据 |
| 收稿时间： | 2019/5/7 0:00:00 |
Comprehensive Risk Assessment of Hazards in Grain Supply Chain Based on Multi-Dimensional Data |
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| WANG Xiaoyi,WANG Zhenni,KONG Jianlei,JIN Xuebo,SU Tingli and ZHANG Xin.Comprehensive Risk Assessment of Hazards in Grain Supply Chain Based on Multi-Dimensional Data[J].Journal of Beijing Technology and Business University:Natural Science Edition,2019,37(6):129-138. |
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| Authors: | WANG Xiaoyi WANG Zhenni KONG Jianlei JIN Xuebo SU Tingli and ZHANG Xin |
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| Institution: | School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China,School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China,School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China,School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China;Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China,School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China and School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China |
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| Abstract: | In order to scientifically and reasonably evaluate the comprehensive risks of heavy metals, mycotoxins, pesticide residues and microorganisms in all aspects of the grain supply chain, based on the analysis of sampling data and other multi-dimensional data of processed grain products from 26 provinces,a large number of multi-dimensional data were transformed into quantitative risk indicators, taken into account the quantitative indicators and qualitative indicators. And multi-dimensional risk indicator system was constructed from three complementary perspectives:statistical characteristics, sampling characteristics and research characteristics. Then the association rules were applied to dig the internal relations among the indicators, realize the weight allocation of each index, construct a comprehensive risk assessment method, and realize the multi-dimensional data-driven grain supply chain hazard risk assessment and prioritization. It might provide a scientific basis for the regulatory authorities to develop targeted sampling strategies, establish priority regulatory areas and allocate risk management resources. |
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| Keywords: | grain hazards supply chain safety multi-dimensional indicators association rules mining risk assessment multi-source heterogeneous data |
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