收藏本站
收藏 | 手机打开
二维码
手机客户端打开本文

Soft Computing for Fast Multidisciplinary Design Optimization

Paul P.Lin  Kenol Jules  
【摘要】:正Multidisciplinary design optimization using the traditional hard computing techniques is difficult to perform mainly due to conflicting design objectives from many different disciplines. This paper describes how computationally efficient Taguchi techniques combined with soft computing such as fuzzy logic and neural networks can be used to perform fast multidisciplinary design optimization. An aircraft engine cycle design optimization with four conflicting design objectives is used to validate the presented approach. The result obtained shows significant performance improvement in optimizing single and multiple design objectives whenever possible conflict exists among them.

知网文化
中国知网广告投放
 快捷付款方式  订购知网充值卡  订购热线  帮助中心
  • 400-819-9993
  • 010-62982499
  • 010-62783978