首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   1篇
  免费   0篇
水路运输   1篇
  2019年   1篇
排序方式: 共有1条查询结果,搜索用时 0 毫秒
1
1.
Coastal defenses such as the breakwaters are important structures to maintain the navigation conditions in a harbor. The estimation of their hydrodynamic characteristics is conventionally done using physical models, subjecting to higher costs and prolonged procedures. Soft computing methods prove to be useful tools, in cases where the data availability from physical models is limited. The present paper employs adaptive neuro-fuzzy inference system(ANFIS) and artificial neural network(ANN) models to the data obtained from physical model studies to develop a novel methodology to predict the reflection coefficient(K_r) of seaside perforated semicircular breakwaters under low wave heights, for which no physical model data is available. The prediction was done using the input parameters viz., incident wave height(Hi), wave period(T), center-to-center spacing of perforations(S), diameter of perforations(D), radius of semicircular caisson(R), water depth(d), and semicircular breakwater structure height(h_s). The study shows the prediction below the available data range of wave heights is possible by ANFIS and ANN models. However, the ANFIS performed better with R~2= 0.9775 and the error reduced in comparison with the ANN model with R~2= 0.9751. Study includes conventional data segregation and prediction using ANN and ANFIS.  相似文献   
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号