...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>The Journal of the Textile Institute >Predicting bending rigidity of woven fabrics using adaptive neuro-fuzzy inference system (ANFIS)
【24h】

Predicting bending rigidity of woven fabrics using adaptive neuro-fuzzy inference system (ANFIS)

机译：使用自适应神经模糊推理系统（ANFIS）预测机织物的抗弯刚度

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

Predictability of the bending rigidity of cotton plain-woven fabrics from their structural parameters has been investigated using an adaptive neuro-fuzzy inference system (ANFIS) approach. A set of cotton grey fabrics meant for apparel end use was desized, scoured, and relaxed. The fabrics were then conditioned and tested for bending properties. Fabric weight, fabric thickness, and fabric cover constituted the input parameters for the model, whereas overall bending rigidity of the fabric was the single output parameter. Fabric data-set has been modeled using ANFIS and its prediction potential is compared with that of an artificial neural network (ANN) model. A sensitivity analysis was also carried out to investigate the robustness of developed model. Results show that the learning capability of the ANFIS model is superior and its generalization ability is slightly better than that of a standalone ANN model.
机译：使用自适应神经模糊推理系统（ANFIS）方法研究了棉平纹织物根据其结构参数可预测的弯曲刚度。将一套用于服装最终用途的棉灰色织物进行了脱浆，精练和放松。然后对织物进行调理并测试其弯曲性能。织物重量，织物厚度和织物覆盖度构成模型的输入参数，而织物的整体抗弯刚度是单个输出参数。织物数据集已使用ANFIS进行建模，并将其预测潜力与人工神经网络（ANN）模型进行了比较。还进行了敏感性分析以研究开发模型的鲁棒性。结果表明，与独立的ANN模型相比，ANFIS模型的学习能力优越，泛化能力略强。

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