Optimal courier matching method and device based on machine learning and computer program product

Optimal courier matching method and device based on machine learning and computer program product

The invention relates to an intelligent courier matching method, in particular to an optimal courier matching method and device based on machine learning and a computer program product. According to the method, the data is collected, the collected data is subjected to standardization and structural...

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Bibliographische Detailangaben
Hauptverfasser: YAN SHUO, CHU MIN, YUAN JIE, LIN KAIWEN, ZHAO YULU, SONG TIANYU, LIU-XU JIQI, XIAO YUJIE, LI JUNLI, LIU YUFEI, ZHU HAO, ZHANG YUNFAN, GUAN YIRUN, CAO JUNRU
Format: Patent
Sprache:chi ; eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:The invention relates to an intelligent courier matching method, in particular to an optimal courier matching method and device based on machine learning and a computer program product. According to the method, the data is collected, the collected data is subjected to standardization and structural processing and feature value label processing, an optimal model algorithm is obtained, and optimal courier matching is achieved through the optimal model algorithm. The method has the following characteristics: 1, the distribution efficiency is improved; 2, the customer satisfaction is improved; 3, optimizing resource allocation; 4, enhancing decision support; and 5, the prediction capability is improved. 本发明涉及快递员智能匹配方法，尤其涉及一种基于机器学习的最优快递员匹配方法、设备和计算机程序产品。该方法通过对数据进行收集，对收集的数据进行标准化和结构化处理，特征值标签处理，获得最优模型算法，通该得最优模型算法实现了最优快递员匹配。本发明具有以下特点：1、提高配送效率；2、提升客户满意度；3、优化资源分配；4、增强决策支持；5、提升预测能力。