...
首页> 外文期刊>The Journal of Chemical Thermodynamics >Estimation of VLE of binary systems (tert-butanol + 2-ethyl-1-hexanol) and (n-butanol + 2-ethyl-1-hexanol) using GMDH-type neural network
【24h】

Estimation of VLE of binary systems (tert-butanol + 2-ethyl-1-hexanol) and (n-butanol + 2-ethyl-1-hexanol) using GMDH-type neural network

机译:使用GMDH型神经网络估算二元系统(叔丁醇+ 2-乙基-1-己醇)和(正丁醇+ 2-乙基-1-己醇)的VLE

获取原文
获取原文并翻译 | 示例

摘要

The group method of data handling (GMDH) method was used to estimate (vapour + liquid) equilibrium (VLE) for the binary systems of (tert-butanol + 2-ethy1-1-hexanol) and (n-butanol + 2-ethy1-1-hexanol). Using this method, a new model was proposed, which is suitable for predicting the VLE data. In this publication, the proposed model was 'trained' before requested predictions. The data set was divided into two parts: 70% were used as data for 'training' (either 10 or 12), and 30% were used as a test set, which were randomly extracted from the database (either 14 or 16). After the training on the input-output process, the predicted values were compared with those of experimental values in order to evaluate the performance of the GMDH neural network method. The model values showed a very good regression with the experimental results.
机译:数据处理的分组方法(GMDH)用于估计(叔丁醇+ 2-ethy1-1-己醇)和(正丁醇+ 2-ethy1)二元系统的(蒸汽+液体)平衡(VLE) -1-己醇)。提出了一种适用于预测VLE数据的新模型。在该出版物中,在要求的预测之前对提出的模型进行了“训练”。数据集分为两个部分:70%用作“训练”数据(10或12),30%用作测试集,从数据库中随机抽取(14或16)。在对输入输出过程进行训练之后,将预测值与实验值进行比较,以评估GMDH神经网络方法的性能。模型值与实验结果显示出很好的回归。

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