• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Fourth UKSim European Symposium on Computer Modeling and Simulation >Modeling and Optimization of a Supply Chain Loop's Performance by an Integrated Neural Network-Fuzzy Regression-Ridge Regression Approach
【24h】

Modeling and Optimization of a Supply Chain Loop's Performance by an Integrated Neural Network-Fuzzy Regression-Ridge Regression Approach

机译：集成神经网络-模糊回归-里奇回归方法对供应链环绩效进行建模与优化

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The goal of this research is to identify the significant factors affecting the firm performance and estimate the system behavior in different operating conditions. By determining the statistical relations of the productivity and effectiveness of the firm with these factors, a decision-making framework can be provided to improve the system performance within the competitive strategy of the whole supply chain. This research presents a flexible meta modeling approach for modeling and optimization the operating performance of a firm in a supply chain by integrating Fuzzy Linear Regression (FLR), Ridge Regression (RR), and Artificial Neural Network (ANN). The efficiencies of FLR, RR and ANN approaches in prediction and modeling are compared and the superior approach is selected according to Mean Absolute Percentage Error (MAPE) and minimum number of observation (n) for test data calculated from OC curve.
机译：这项研究的目的是确定影响公司绩效的重要因素，并估计不同操作条件下的系统行为。通过确定企业生产率和效率与这些因素之间的统计关系，可以提供决策框架来改善整个供应链竞争策略中的系统绩效。这项研究提出了一种灵活的元建模方法，通过集成模糊线性回归（FLR），岭回归（RR）和人工神经网络（ANN）对供应链中的公司的运营绩效进行建模和优化。比较了FLR，RR和ANN方法在预测和建模中的效率，并根据从OC曲线计算出的测试数据的平均绝对百分比误差（MAPE）和最小观察次数（n）选择了更好的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号