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Shear strength prediction of Ni-Ti alloys manufactured by powder metallurgy using fuzzy rule-based model

机译:基于模糊规则的粉末冶金镍钛合金的剪切强度预测

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摘要

Powder metallurgy is an important manufacturing method and developing models that can predict the characteristics of the products is remarkable for researchers. There are many models discussed in the literature for prediction of the product properties however, nonlinear modeling methods including artificial neural networks (ANNs) and fuzzy models have shown better performance.rnIn the present work, a rule-based fuzzy logic model is developed to predict the shear strength of Ni-Ti alloys specimens manufactured by powder metallurgy method. The processing time and temperature are selected as the input variables and a fuzzy model is designed with two inputs and one output variable. Four statistical parameters are used for assessment of the model accuracy. The comparison of this model result and the result of the ANN model that have been reported by previous researchers, shows that the fuzzy model is more accurate and actually better than ANN model for predicting the shear strength of Ni-Ti alloys specimens manufactured by powder metallurgy.
机译:粉末冶金是一种重要的制造方法,可以预测产品特性的开发模型对于研究人员而言非常重要。文献中讨论了许多用于预测产品性能的模型,但是,包括人工神经网络(ANN)和模糊模型在内的非线性建模方法表现出更好的性能。rn在当前工作中,开发了基于规则的模糊逻辑模型来预测产品性能。粉末冶金法制备的镍钛合金试样的剪切强度。选择处理时间和温度作为输入变量,并设计具有两个输入和一个输出变量的模糊模型。四个统计参数用于评估模型的准确性。该模型结果与先前研究人员报告的ANN模型结果的比较表明,在预测粉末冶金生产的Ni-Ti合金试样的剪切强度时,模糊模型比ANN模型更准确,实际上更好。

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