Magnetic Field Extrapolation Based on Improved Back Propagation Neural Network

Chen, Xiao; Liu, Shengdao; Zhou, Guohua; Yang, Mingming

doi:10.1007/978-3-642-16530-6_9

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…G.H. Zhou [7] has studied the localization of a magnetic object based on Hopfield neural network and L T Lian [8] has got upper air magnetic field from underwater ones by an improved BP neural network.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Anomaly Evaluation Based on Linear Neutral Network

Chen

Yang

Zhou

2011

2011 3rd International Workshop on Intelligent Systems and Applications

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The magnetic anomaly created by ferromagnetic ships may endanger their invisibility. Nowadays, a new technique called closed-loop degaussing system can reduce the magnetic anomaly especially permanent one in real-time. To achieve it, a model able to predict off-board magnetic field from onboard measurements is required. Many researchers settle the problem by some numerical models. In this paper, we propose a linear neural network to solve it. The method can avoid many problems from linear model. Its high accuracy and good generalization ability have been tested by a mockup experiment.

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Section: Introductionmentioning

confidence: 99%

Magnetic Anomaly Evaluation Based on Linear Neutral Network

Chen

Yang

Zhou

2011

2011 3rd International Workshop on Intelligent Systems and Applications

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“…G.H. Zhou [8] has studied the localization of a magnetic object based on Hopfield neural network and L T Lian [9], [10]has got upper air magnetic field from underwater ones by an improved BP neural network and got offboard magnetic field from onboard ones by a linear neural network .…”

Section: Introductionmentioning

confidence: 99%

Degaussing currents optimal calibration method based on linear neutral network

Zhao¹,

Yang²,

Xu³

2013

Proceedings of 2013 3rd International Conference on Computer Science and Network Technology

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The magnetic field created by ferromagnetic ships may endanger their invisibility. Nowadays, a new technique called closed-loop degaussing system can reduce the magnetic anomaly especially permanent one in real-time. The key technique of this system is to predict degaussing currents from onboard measurements. To achieve it, researchers often solve the problem by Offboard Magnetic Field Method (OMFM) or Coils' Current Database Method (CCDM). In this paper, a linear neural network has been proposed to get the currents directly from onboard magnetic field. The neural network can prevent many troubles from other methods. Its high precision and good robustness have been tested by a mockup test.

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Evaluation of Underwater Target Scheme Based on Improved Back Propagation Neural Network

Yang¹

2019

Advances in Intelligent, Interactive Systems and Applications

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Magnetic Field Extrapolation Based on Improved Back Propagation Neural Network

Cited by 4 publications

References 7 publications

Magnetic Anomaly Evaluation Based on Linear Neutral Network

Magnetic Anomaly Evaluation Based on Linear Neutral Network

Degaussing currents optimal calibration method based on linear neutral network

Evaluation of Underwater Target Scheme Based on Improved Back Propagation Neural Network

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