【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。更多还原

【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.更多还原