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首页> 外文期刊>The Journal of the Textile Institute >A multilayer perceptron artificial neural network model for estimation of ultraviolet protection properties of polyester microfiber fabric
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A multilayer perceptron artificial neural network model for estimation of ultraviolet protection properties of polyester microfiber fabric

机译：涤纶超细纤维织物紫外保护性能估计多层的感知人工神经网络模型

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摘要

In this study, the use of a polyester fabric produced from microfibers as a siding material for construction industry was investigated. In this context, an ultraviolet (UV) absorber was applied to the polyester fabric samples with and without dyeing process. These samples were treated with UV absorber at 1-4% concentration and then an accelerated aging test was carried out. The UV absorbance capacity of the samples was investigated before and after the accelerated aging test. Furthermore, the effects of dyeing process on UV absorbance capacity of samples were analyzed. Afterwards, a multilayer perceptron artificial neural network (MLP-ANN) model was proposed and utilized to predict the UV protection properties which are UV protection factor, UV-A and UV-B in polyester microfiber fabric. The MLP-ANN based results demonstrate that the regression (R) values are almost 1 for all UV protection properties. Accordingly, it was seen that the proposed MLP-ANN is correctly modeled and the prediction of UV protection properties is successfully performed.
机译：在本研究中，研究了从微纤维生产的聚酯织物作为建筑工业的壁板。在这种情况下，用染色方法将紫外（UV）吸收剂施加到聚酯织物样品上。将这些样品用UV吸收剂处理1-4％浓度，然后进行加速老化试验。在加速老化试验之前和之后研究样品的紫外光吸收能力。此外，分析了染色过程对样品的紫外光吸收能力的影响。之后，提出了一种多层感知人工神经网络（MLP-ANN）模型，用于预测紫外保护性质，其在聚酯微纤维织物中是UV保护因子，UV-A和UV-B。 MLP-ANN基结果表明，所有UV保护特性的回归（R）值几乎是1。因此，看出所提出的MLP-ANN被正确建模并成功地进行UV保护性能的预测。

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