首页> 外文会议>Symposium of International Rubber Conference >Predicting properties of EPDM vulcanizates by using artificial neural network
【24h】

Predicting properties of EPDM vulcanizates by using artificial neural network

机译:使用人工神经网络预测EPDM硫化胶的性质

获取原文

摘要

In this paper, artificial neural network (ANN) was applied to forecast the properties of EPDM Vulcanizates. Twenty groups of experiment results designed by the method of current rotational and combinatorial design of quadratic regression with three factors were used as the training samples of ANN. Back-Propagation (BP) neural network was established by the neural network tool of MATLAB (MATrix LABoratory software) version 6.5 and the optimum parameters of ANN were chosen. Through training the BP neural network, the well-trained ANN is expected to be very helpful for prediction of EPDM vulcanizates properties including oxygen indexes, tensile strength and elongation at break. The results show that the well-trained ANN can exactly forecast the EPDM vulcanizates properties. ANN based on MATLAB 6.5 also offers an efficient and credible method on analyzing the effect of EPDM vulcanizates' components.
机译:本文采用人工神经网络(ANN)预测EPDM硫化胶的性质。通过电流旋转和组合设计的二十二个旋转和三种因素的组合设计设计的二十多组实验结果用作ANN的训练样本。由MATLAB(矩阵实验室软件)版本6.5的神经网络工具建立了后传播(BP)神经网络,选择了ANN的最佳参数。通过培训BP神经网络,训练有素的ANN预计对预测EPDM硫化物质的性能非常有助于包括氧指数,拉伸强度和断裂处的伸长率。结果表明,训练有素的安格尔可以完全预测EPDM硫化物属性。基于MATLAB 6.5的ANN还提供了一种有效且可靠的方法,可分析EPDM硫化杂质组件的效果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号