...
首页> 外文期刊>Applied solar energy >Artificial Neural Networks Approach on Solar Parabolic Dish Cooker1
【24h】

Artificial Neural Networks Approach on Solar Parabolic Dish Cooker1

机译:太阳能抛物面炊具的人工神经网络方法

获取原文
获取原文并翻译 | 示例

摘要

This paper presents heat transfer analysis of solar parabolic dish cooker using Artificial Neural Network (ANN). The objective of this study to envisage thermal performance parameters such as receiver plate and pot water temperatures of the solar parabolic dish cooker by using the AN N for experimental data. An experiment is conducted under two cases (1) cooker with plain receiver and (2) cooker with porous receiver. The Back Propagation (BP) algorithm is used to train and test networks and ANN predictions are compared with experimental results. Different network configurations are studied by the aid of searching a relatively better network for prediction. The results showed a good regression analysis with the correlation coefficients in the range of 0.9968-0.9992 and mean relative errors (MREs) in the range of 1.2586-4.0346% for the test data set. Thus ANN model can successfully be used for the prediction of the thermal performance parameters of parabolic dish cooker with reasonable degree of accuracy.
机译:本文介绍了使用人工神经网络(ANN)的太阳能抛物面炊具的传热分析。这项研究的目的是通过将AN N用于实验数据来设想热性能参数,例如太阳能抛物面炊具的接收盘和锅水温度。在以下两种情况下进行实验:(1)带普通接收器的炊具和(2)带多孔接收器的炊具。反向传播(BP)算法用于训练和测试网络,并将ANN预测与实验结果进行比较。通过搜索相对更好的网络进行预测来研究不同的网络配置。结果显示了良好的回归分析,对于测试数据集,相关系数在0.9968-0.9992的范围内,平均相对误差(MRE)在1.2586-4.0346%的范围内。因此,ANN模型可以成功地以合理的准确度用于抛物面炊具的热性能参数的预测。

著录项

  • 来源
    《Applied solar energy 》 |2011年第4期| p.312-317| 共6页
  • 作者单位

    National Institute of Technology;

    Adhiyamaan College of Engineering, India;

  • 收录信息 美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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