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基于神经网络的固体火箭发动机比冲性能的预示研究

THE PREDICTION OF THE SPECIFIC IMPULSE FOR SOLID PROPELLANT ROCKET ENGINE BASED ON ARTIFICIAL NEURAL NETWORK

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【作者】 张宇星邱志平段志信

【Author】 ZHANG Yu-xing1 , *QIU Zhi-ping1 , DUAN Zhi-xin2 (1. Institute of Solid Mechanics, Beijing University of Aeronautics and Astronautics, Beijing 100083, China; 2. The Department of Basic Science, Inner Mongolia University of Technology, Hohhot 010062, China)

【机构】 北京航空航天大学固体力学研究所内蒙古工业大学理学院 北京100083北京100083呼和浩特010062

【摘要】 将神经网络方法引入了固体火箭发动机的比冲性能预测,该方法避开了系统具体规律分析以及相应数学模型建立所带来的困难,直接用神经网络模型来模拟真实的系统关系。采用了一种改进的Ⅱ型RBF神经网络,克服了传统的RBF神经网络径向基函数个数未知的缺陷,并将其预测结果与传统的BP神经网络的预测结果进行了比较。

【Abstract】 The artificial neural networks are applied to the prediction of the specific impulse for solid propellant rocket engine. This method avoids the difficulties of concrete law analysis and the mathematical modeling. We can obtain directly the network model which contains the relation of actual system. An improved radial basis function neural networks is presented, which compensates the defect of undiscovered number of radial basis function for the traditional radial basis function neural networks. The forecast results of radial basis function neural networks and back propagation learning algorithm are compared.

  • 【文献出处】 工程力学 ,Engineering Mechanics , 编辑部邮箱 ,2006年S1期
  • 【分类号】V435
  • 【被引频次】1
  • 【下载频次】146
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