首页> 外文会议>WRI World Congress on Computer Science and Information Engineering >Study on Response Surface Methodology with Artificial Neural Networks Application in Aerodynamic Optimization
【24h】

Study on Response Surface Methodology with Artificial Neural Networks Application in Aerodynamic Optimization

机译:基于人工神经网络的响应面方法在气动优化中的应用研究。

获取原文
获取外文期刊封面目录资料

摘要

Response surface methodology is currently commonly used and solutes to engineering design aerodynamic optimization problem. Artificial neural networks is the familiar approximation methods. It is trained and tested using a relatively small number of high fidelity CFD flow simulations. The ANN approximation was found to save on the simulation computation time and improved the generalization capability of the ANN model by reducing the overtraining or memorization problem.
机译:响应面方法目前常用并溶于工程设计空气动力学优化问题。人工神经网络是熟悉的近似方法。它使用相对少量的高保真CFD流模拟训练和测试。发现ANN近似是通过减少过度训练或记忆问题来节省仿真计算时间并改善了ANN模型的泛化能力。

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