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Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network
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WU Xiao-guang[1,2] SHI Zhong-kun[1]
[1]College of Traffic Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China [2]China Ship Development and Design Center, Wuhan 430064, China
文章出处:
《船舶与海洋工程学报：英文版》-2006年5卷2期 -36-41页
Journal of Marine Science and Application
分 类 号:
文献标识码:
A
文章编号:
1671-9433（2006）02-0036-06
相关文章:
Underwater vehicle sonar self-noise prediction based on genetic algorithms and neural network
WU;Xiao-guang;SHI;Zhong-kun
Abstract:
The factors that influence underwater vehicle sonar self-noise are analyzed, and genetic algorithms and a back propagation （BP） neural network are combined to predict underwater vehicle sonar self-noise. The experimental results demonstrate that underwater vehicle sonar self-noise can be predicted accurately by a GA-BP neural network that is based on actual underwater vehicle sonar data.[著者文摘]
Key words:
sonar self-noise; back propagation （BP） neural network; genetic algorithms
收稿日期: 2005-06-27
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