【摘要】 对物流网环境下区域物流量进行预测,能够对区域物流服务人员进行调整,对提高区域物流服务水平具有重要意义。针对当前区域物流量预测方法存在的预测精确度低,预测过程复杂,运行占用网络内存较大问题,提出一种基于支持向量机的物联网环境下区域物流量预测方法。利用主成分分析的方法,通过计算区域物流量影响因素的特征值和特征向量,提取区域物流量新综合变量。利用支持向量机方法,根据提取的区域物流量新综合变量,建立区域物流量预测模型,并对模型的损失函数进行优化,确定区域物流量预测的目标函数,根据目标函数,实现区域物流量预测。实验结果表明,所提方法预测的精确度较高,且预测速度较快,运行占用的网络内存较少。更多还原

【Abstract】 To predict the regional logistics volume in logistics network environment can improve the service level of regional logistics.At present,the method has the problem of low prediction accuracy and complex prediction process.Therefore,this paper focuses on a method to predict regional logistics volume in Internet of Things environment based on support vector machine.Through calculating the eigenvalue and feature vector of influencing factors of regional logistics volume,the method of principal component analysis was used to the new comprehensive variable of regional logistics volume.Then,the support vector machine method was used to build the model for prediction regional logistics volume based on new comprehensive variable of regional logistics volume.Meanwhile,the loss function of model was optimized to determine the objective function predicted by regional logistics volume.Thus,the prediction of regional logistics volume was achieved based on objective function.Simulation results prove that the proposed method has the higher prediction accuracy and faster prediction and uses less network memory.更多还原