首页|基于大数据融合的应急物资可追溯信息挖掘模型构建

基于大数据融合的应急物资可追溯信息挖掘模型构建

扫码查看
传统的应急物资信息方法受到应急物资信息类型以及来源的影响,导致追溯效果不佳.为此,构建基于大数据融合的应急物资可追溯信息挖掘模型.选取巴科斯-诺尔范式规范化描述对应急物资可追溯信息,采用大数据融合匹配应急物资信息追溯结果.通过Dasarathy信息融合模型设计三层递进模式,利用EM算法建立挖掘模型,实现对应急物资可追溯信息的有效挖掘.实验结果表明,采用该模型可有效挖掘应急物资可追溯信息,不同情况下挖掘精度均高于99%,并具有较高的实时性.
CONSTRUCTION OF TRACEABLE INFORMATION MINING MODEL FOR EMERGENCY MATERIALS BASED ON BIG DATA FUSION
The traditional emergency material information method is affected by the type and source of emergency material information,which makes the tracing effect poor.Therefore,a traceability information mining model of emergency materials based on big data fusion is constructed.This paper selected Bakos Noel paradigm to describe the traceability information of emergency supplies,used big data fusion to match the traceability results of emergency materials information,designed a three-level progressive mode through Dasarathy information fusion model,and established a mining model using EM algorithm to realize the effective mining of traceable information of emergency supplies.The experimental results show that the model can effectively mine the traceability information of emergency materials,and the mining accuracy is higher than 99%in different situations,and has high real-time performance.

Big data fusionEmergency suppliesTraceable informationMining model

刘佳、陈雪莲、连鸿波

展开 >

国网江西省电力物资有限公司 江西南昌 330000

国网江西省电力有限公司信息通信分公司 江西南昌 330000

国网上海松江供电公司 上海 200000

大数据融合 应急物资 可追溯信息 挖掘模型

国网江西省电力有限公司重点项目

711835180059

2024

计算机应用与软件
上海市计算技术研究所 上海计算机软件技术开发中心

计算机应用与软件

CSTPCD北大核心
影响因子:0.615
ISSN:1000-386X
年,卷(期):2024.41(4)
  • 15