基于多类信息融合划分的物流信息调度模型设计

摘要

提出一种基于多类信息融合划分的物流差异信息调度模型。利用双重扩展卡尔曼滤波方法，对多类信息进行融合处理，从而消除物流数据之间的差异性，为多类信息融合划分提供依据。利用支持向量机方法，对融合后的多类物流相关信息进行分类，根据获取的分类物流信息，完成物流信息调度模型的设计。实验结果表明，利用该算法进行物流信息调度模型设计，能够为调度提供准确的物流信息，从而满足物流信息管理的实际需求。%In this paper, we proposed a logistics differential information scheduling model on the basis of multi-categorial information fusion and classification to eliminate the incompatibility among the logistics data. Next we used the support vector machine approach to classify the multiple categories of logistics information which were relevant and finished the design of the logistics information scheduling model. At the end, through an experiment, we demonstrated that the algorithm could yield accurate logistics information and satisfy the practical need in logistics information management.