• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied mathematics and computation >Smart case-based indexing in worsted roving process: Combination of rough set and case-based reasoning
【24h】

Smart case-based indexing in worsted roving process: Combination of rough set and case-based reasoning

机译：精纺粗纱过程中基于案例的智能索引：粗糙集与基于案例的推理相结合

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Rough set data analysis (RSDA) has been primarily studied in order to obtain knowledge rules. Taking one group of data as an example, according to the simplified attributes and extractive rules a case was established; using case-based reasoning (CBR), another case was established based on the parameters influencing on the roving quality. In addition, RSDA was combined with CBR to build the case library. This allowed unimportant parameters to be removed and the case library to be simplified; in turn allowing easier, more effi_cient searching of attributes from the simplified case library. The union of Rule-Based Reasoning (RBR) and CBR means that complicated calculations around similar cases and the associated error can be avoided. Using RSDA one is able to reveal characteristic attributes and deduce knowledge rules associated with the model problem in order to build a case library directly from historical data. So using the above procedure, allows machine settings to be defined and the prediction and control of the end-product quality to be easier.
机译：为了获得知识规则，已经对粗糙集数据分析（RSDA）进行了初步研究。以一组数据为例，根据简化属性和提取规则，建立了一个案例。使用基于案例的推理（CBR），基于影响粗纱质量的参数建立了另一个案例。此外，RSDA与CBR结合在一起构建了案例库。这样就可以删除不重要的参数，并简化案例库。进而允许从简化案例库中更轻松，更有效地搜索属性。基于规则的推理（RBR）和CBR的结合意味着可以避免围绕相似案例和相关错误进行复杂的计算。使用RSDA可以揭示特征属性并推论与模型问题相关的知识规则，以便直接从历史数据中构建案例库。因此，使用上述过程，可以定义机器设置，并更轻松地预测和控制最终产品的质量。

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