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Computer aided optimum design of friction materials using uniform design

机译:采用统一设计的计算机辅助摩擦材料的优化设计

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The application of Uniform design in friction material formulation and a multi-layer back propagation artificial neural network (BPANN) methods of Data Handling are investigated for modeling and prediction of the wear properties of composites. The friction and wear properties show that Uniform design can distribute the experiment points evenly so as to have fewer number of tests. With computer aided artificial neural network (ANN) modeling and optimization technology, the relationships between factors and properties can be predicted.
机译:研究了均匀设计在摩擦材料配方中的应用以及数据处理的多层反向传播人工神经网络(BPANN)方法对复合材料的磨损特性进行建模和预测。摩擦磨损性能表明,均匀设计可以均匀分布实验点,从而减少了测试次数。利用计算机辅助人工神经网络(ANN)建模和优化技术,可以预测因素与属性之间的关系。

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