Tensile Strength Prediction of Polyethylene Terephthalate Bottle Ropes using Neuro - fuzzy

D. Pacis, Edwin D. C. Subido, R. Baldovino, N. Bugtai
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引用次数: 1

Abstract

With the huge amounts of plastic bottles being consumed and disposed daily, people have been using different techniques to recycle. One way is to convert them into strings that will be made into plastic ropes. This paper aims to predict the tensile strength of polyethylene terephthalate (PET) bottle ropes using neuro-fuzzy approach given the following inputs: average thickness of strand, strand width, and the number of strands used. Actual data parameters from a previous research, applying design of experiment (DOE), will be utilized as the training and testing data of the network. Moreover, a comparison between the outputs of the neuro-fuzzy model and the statistical model will be shown. The generated fuzzy rules will be analyzed at certain conditions and compared with the optimization results of previous research. Results showed that although the network has very low training errors, testing errors were higher than acceptable values.
用神经模糊法预测聚对苯二甲酸乙二醇酯瓶绳的拉伸强度
随着每天大量的塑料瓶被消耗和丢弃,人们一直在使用不同的技术来回收利用。一种方法是将它们转换成绳子,再制成塑料绳。本文旨在利用神经模糊方法预测聚乙烯对苯二甲酸乙二醇酯(PET)瓶绳的抗拉强度,给出以下输入:股的平均厚度,股的宽度,和所用股的数量。应用实验设计(DOE)中的实际数据参数将被用作网络的训练和测试数据。此外,将显示神经模糊模型和统计模型的输出之间的比较。将生成的模糊规则在一定条件下进行分析,并与前人研究的优化结果进行比较。结果表明,虽然网络的训练误差很低,但测试误差高于可接受值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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