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 :
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