DocumentCode
3345313
Title
Ship Hydrodynamic Pressure Signal Detection Based on Neural Network Prediction
Author
Zhang Xiaobing ; Jia Yizhuo
Author_Institution
Dept. of Weaponry Eng., Naval Univ. of Eng., Wuhan, China
fYear
2009
fDate
14-17 Oct. 2009
Firstpage
469
Lastpage
471
Abstract
The ship hydrodynamic pressure signal is generally hard to detect from the rough ocean wave hydrodynamic pressure background signal. An algorithm based on neural network prediction is provided to detect the ship pressure signal from the ocean wave pressure signal. The predictions of hydrodynamic pressure signal are compared with measurements of the same variables to form prediction errors that are used to test for the presence of the ship pressure signal. If the prediction errors are relatively high, it will mean the appearance of a ship hydrodynamic pressure signal. Through the simulation results on the simulated and the measurement data, the algorithm based on feed forward neural network prediction proved its validity.
Keywords
error analysis; feedforward neural nets; hydrodynamics; ocean waves; prediction theory; ships; signal detection; feedforward neural network prediction; ocean wave pressure signal; prediction errors; ship hydrodynamic pressure signal detection; Feeds; Hydrodynamics; Marine vehicles; Neural networks; Ocean waves; Predictive models; Pressure measurement; Sea measurements; Signal detection; Testing; error; neural network; prediction; ship hydrodynamic pressure;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
Conference_Location
Guilin
Print_ISBN
978-0-7695-3899-0
Type
conf
DOI
10.1109/WGEC.2009.173
Filename
5402795
Link To Document