摘要
现有预测模型预测误差时间大、修正效果差,因此研究考虑天气状况的农产品冷链物流配送预测模型。首先,选取农产品冷链物流配送预测指标,运用灰度关联度根据目标系统中农产品冷链物流的需求和不同天气状况的几何形状的接近程度来判断关联度。其次,根据不同的关联度划分关联等级,将其进行分类。再次,通过构建区域物流模型判断节点之间是否存在连接。最后,在矩阵中添加权重描述不同节点之间的连接关系,计算网络中节点之间的最短路径,从而完成预测模型构建。实验结果表明,实验组的预测误差时间结果为4组最小,相对其他小组平均预测误差时间缩短了10 s左右,达到较准确的预测结果,使得冷链物流配送预测模型的应用效果更佳。
Because the existing prediction model has the large prediction error time and the poor correction effect,the cold chain logistics prediction model of agricultural products distribution considering the weather conditions is studied.Firstly,the prediction index of agricultural cold chain logistics distribution is selected,and the gray correlation degree is judged according to the proximity of agricultural cold chain logistics demand and the geometric shape of different weather conditions in the target system.Secondly,the association levels are divided according to the different correlation degrees,and they are classified.Thirdly,determine whether there is a connection between the nodes by constructing a regional logistics model.Finally,add weights to the matrix to describe the connections between different nodes,and calculate the shortest path between the nodes in the network so as to complete the prediction module construction.The experimental results show that the prediction error time of the experimental group is the smallest in the four groups,and the average prediction error time of the other groups is shortened by about 10 s,so as to achieve more accurate prediction results,which makes the application effect of the cold chain logistics distribution prediction model better.
作者
王伟
焦小炜
WANG Wei;JIAO Xiaowei(Hebei Traffic Vocational and Technical College,Shijiazhuang Hebei 050035,China)
出处
《信息与电脑》
2023年第11期192-194,共3页
Information & Computer
关键词
农产品
冷链物流配送
预测模型
天气
agricultural products
cold chain logistics distribution
forecast model
weather
