Logistics service evaluation method and system based on data mining
By integrating multi-source data and implementing a dynamic evaluation closed loop, the problems of human subjectivity and data fragmentation in logistics service evaluation have been solved. This has enabled accurate and quantifiable evaluation of logistics service quality and the generation of optimization strategies, thereby improving the accuracy and real-time nature of the evaluation results.
Patent Information
- Authority / Receiving Office
- CN Β· China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HONGYUN HONGHE TOBACCO (GRP) CO LTD
- Filing Date
- 2026-04-20
- Publication Date
- 2026-07-17
AI Technical Summary
Existing logistics service evaluation methods rely on subjective human judgment, lack sufficient data support, have single evaluation indicators, fragmented data, and lack dynamic adjustment and linkage, resulting in large deviations in evaluation results and failing to reflect the true service level or provide optimization guidance.
By integrating multi-source data, using the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation, and combining them with the Apriori association rule algorithm, a dynamic evaluation closed loop is constructed to achieve a comprehensive and objective assessment of logistics service quality and generate optimization strategies.
It enables precise, quantifiable evaluation and dynamic optimization of logistics service quality, reduces human subjective bias, improves the accuracy and real-time nature of evaluation results, and forms a closed-loop mechanism of evaluation-optimization-improvement.
Smart Images
Figure CN122414907A_ABST