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The Model of Ship’s Magnetic Field Extrapolation Based on Neural Network Improved by Particle Swarm Optimization |
LIAN Li-Ting, XIAO Chang-Han, YANG Ming-Ming, ZHOU Guo-Hua |
(School of Electrical and Information Engineering, Naval University of Engineering, Wuhan 430033, China) |
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Abstract The magnetic anomaly created by ferromagnetic submarines may endanger their invisibility. Nowadays, a new technique called closedloop degaussing system can reduce the magnetic anomaly especially permanent one in realtime. To achieve it, a model which is able to predict offboard magnetic field from on board measurements was required. Many researchers settle the problem by a linear model. A back propagation neural network model was proposed to solve it. The model can escape local optimum thanks to optimizing the initial weight values and threshold values by particle swarm optimization algorithm. The method can avoid many problems from linear model and its high accuracy and good robustness was tested by a mockup experiment.
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Received: 10 July 2010
Published: 29 June 2011
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