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《Ordnance Industry Automation》 2011-01
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Simulation on Missile Spares Demands Prediction Based on RBF Neural Network

Yan Gang1,Zhou Wensong2,Wang Xiangfei1,Gao Hongliang3(1.Administrant Brigade of Postgraduate,Naval Aeronautical & Astronautical University,Yantai 264001,China; 2.Dept.of Training,Naval Aeronautical & Astronautical University,Yantai 264001,China; 3.System Institute of Navy Equipment Research Academy,Beijing 100073,China)  
There are plenty of factors affecting a missile fittings demands,introduce the RBF method.Adopt the certain type missile as the forecasting object,and analyze the factors influencing missile maintenance spare part,introduce the structure,working principle,forecasting steps and flow chart of RBF network,and analyze the simulation result.The analyzing result shows that the method can use less time to solve the forecasting method of spare part requirement than ordinary RBF network.
【CateGory Index】: TJ760
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