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Predictive performance model in collaborative supply chain using decision tree and clustering technique

机译:使用决策树和聚类技术的协同供应链预测性能模型

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This paper proposes an integrated framework between B2B supply chains (B2B-SC) and performance evaluation systems. This framework is based on data mining techniques, enabling the development of a predictive collaborative performance evolution model and decision making which has forward-looking collaborative capabilities. The results are deployment for collaborative performance guidelines, which were validated by the domain experts in terms of its real practical usage efficiency. This framework enables managers to develop systematic manners to predict future collaborative performance and recognize latent problems in their relationship. Its usages and difficulties were also discussed. Furthermore, the final predictive results and rules contain vital information relating to SC improvement in the long term.
机译:本文提出了B2B供应链(B2B-SC)和性能评估系统之间的集成框架。 该框架是基于数据挖掘技术,从而能够开发预测协作性能演化模型和决策,具有前瞻性的协作能力。 结果是在其实际实际使用效率方面由领域专家验证的协同绩效指南的部署。 该框架使管理人员能够开发系统的举止,以预测未来的协作表现,并在其关系中识别潜在问题。 还讨论了它的用法和困难。 此外,最终的预测结果和规则包含长期与SC改进有关的重要信息。

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