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首页> 外文期刊>The Journal of the Textile Institute >A study on siro, solo, compact, and conventional ring-spun yarns. Part Ⅲ: modeling fiber migration using modular adaptive neuro-fuzzy inference system
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A study on siro, solo, compact, and conventional ring-spun yarns. Part Ⅲ: modeling fiber migration using modular adaptive neuro-fuzzy inference system

机译：对siro，solo，紧密和常规环锭纱的研究。第三部分：使用模块化自适应神经模糊推理系统对纤维迁移进行建模

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摘要

The importance of fiber migration in spun yarns as a means of securing cohesion and strength has been emphasized in the literature. However, analyzing migration behavior of fibers is a time-consuming and tedious task. A three-stage hybrid model was developed to estimate yarn migratory properties based on some physical and mechanical properties of spun yarns. Achieving the objectives of this research, general physical, mechanical, and structural properties of spun yarns together with existing standards were thoroughly studied. At the first stage, using stepwise regression analysis, key variables were selected. At the second stage, data-set was clustered into subpopulations by means of K-means in order to decrease effects of noise, rebate complexity of the patterns, and develop a modular model. At the third stage, using adaptive neuro-fuzzy inference system, the target value was predicted. Finally, evaluation of the proposed model was carried out by applying it on the test set.
机译：文献中已经强调了纤维在短纤纱中迁移作为确保内聚力和强度的重要性。但是，分析光纤的迁移行为是一项耗时且繁琐的任务。建立了一个三阶段混合模型，以基于细纱的某些物理和机械性能来估计纱线迁移性能。为了达到本研究的目的，对细纱的一般物理，机械和结构性能以及现有标准进行了彻底的研究。在第一阶段，使用逐步回归分析，选择了关键变量。在第二阶段，通过K均值将数据集聚为亚群，以减少噪声的影响，降低图案的复杂度并开发模块化模型。在第三阶段，使用自适应神经模糊推理系统预测目标值。最后，通过将其应用于测试集来对所提出的模型进行评估。

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