基于径向基神经网络的舰艇磁场推算模型  

Model of Ship's Magnetic Field Extrapolation Based on Radial Basis Function Neural Network

作　　者：连丽婷[1] 杨明明[1] 

机构地区：[1]91388部队

出　　处：《舰船电子工程》2013年第5期161-162,171,共3页Ship Electronic Engineering

基　　金：国家海洋专项基金资助项目(420050101)资助

摘　　要：针对目前数值建模解决舰艇内外磁场推算问题时存在的困难,从智能优化的角度出发,建立了内外磁场之间的径向基神经网络预报模型。该方法避免了利用数值建模存在的诸多困难,即可实现舰艇内外磁场有效推算,并利用船模实验验证了网络预测的准确性,其换算精度相较于数值建模有所提高,满足工程实际需求。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 especialIy 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, a Radial Basis Function（RBF）neural network is proposed 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.

关 键 词：舰船 磁场 闭环消磁 径向基 神经网络 

分 类 号：TM153.1[电气工程—电工理论与新技术]