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Yield strength prediction for thermoplastic composites based on a Sparse Fuzzy Model

机译:基于稀疏模糊模型的热塑性复合材料屈服强度预测

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Nowadays thermoplastic composites are commonly used owing to their good mechanical properties, which can be ensured only by the proper mixing of different types of materials. In this paper, we present the results of our studies regarding the fuzzy modeling of the relation between the yield strength and the amount of the used components (ABS, polycarbonate, multiwall carbon nanotube). The initial rule base was created using FCM clustering and the parameters were tuned by RBE-SI that applies a hill-climbing approach and enriches the rule base with new rules if it is necessary. Owing to the possible sparse character of the rule base the fuzzy rule interpolation based FRIPOC method was used as inference technique. The model was validated by applying it to an independent set of test data.
机译:如今,热塑性复合材料由于其良好的机械性能而被普遍使用,只有通过适当混合不同类型的材料才能确保这种性能。在本文中,我们介绍了关于屈服强度与所用成分(ABS,聚碳酸酯,多壁碳纳米管)数量之间的关系的模糊建模的研究结果。初始规则库是使用FCM聚类创建的,参数是通过RBE-SI进行调整的,RBE-SI应用爬山方法,并在必要时用新规则丰富了规则库。由于规则库的稀疏性,将基于模糊规则插值的FRIPOC方法用作推理技术。通过将模型应用于独立的测试数据集来验证该模型。

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