零担货物快递服务公司自动匹配研究

Research on Automatic Matching of LCL Express Service Company

研究零担货物快递服务公司自动匹配,研究SVM自动匹配方法,依据零担货物快递服务需求自动匹配出最适合的快递公司,研究方法是基于机器学习,借助已有的人工匹配数据构建的数据集,通过python编程,用训练集训练零担货物快递服务公司自动匹配的机器学习模型,验证集验证自动匹配效果。验证集评估结果表明,SVM自动匹配方法,根据零担需求进行快递服务公司的自动匹配,匹配时间仅为1.89 s,精度达到0.90,自动匹配方法能够高效恰当地为零担需求匹配出适合的快递公司,使得零担货物快递的供需双方高度契合。本文研究可以帮助物流服务公司节约匹配成本,提高匹配效率,增强公司竞争力,同时为机器学习中SVM的应用提供思路和参考依据。

Automatic matching of LCL express service company and the SVM automatic matching method are researched.The purpose is to automatically match the most suitable express company according to the service demand of LCL Express.The research method is based on machine learning.with the help of the existing artificial matching data to build the data set.Through python programming,the training set is used to train the machine learning model of the automatic matching of the LCL express service company,and the verification set is used to verify the automatic matching effect.The evaluation results of the verification set show that the automatic matching time of express service company based on the LCL demand is only 1.89 s,and the matching accuracy reaches 0.90.The automatic matching model can efficiently and appropriately match the express service company for the LCL demand.The supply and demand of LCL Express service are suitable.This study can help logistics service companies to save matching costs,improve matching efficiency,and enhance their competitiveness.Meanwhile,it can provide ideas and reference for machine learning application in the era of artificial intelligence.