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飞机结冰严重威胁着飞行安全。针对机翼结冰冰型预测时不确定性因素较多、难以准确预测的问题,提出了一种基于回归型支持向量机的机翼结冰冰型预测方法。在建立冰型模型的基础上,利用回归型支持向量机(Support Vector Regression,SVR)获得冰型多项式系数,从而预测出相关飞行条件和大气条件下的冰型。仿真结果表明,该方法具有较好的预测能力,可以及时提供可靠的结冰信息,为保证结冰条件下的飞行安全提供了保障。
Plane icing seriously threatens flight safety. Aiming at the problem that the ice icing prediction is more uncertain and difficult to predict accurately, a new ice icing forecasting method based on regression support vector machine is proposed. On the basis of establishing the ice model, the ice polynomial coefficients were obtained by using Support Vector Regression (SVR) to predict the ice conditions under the relevant flight conditions and atmospheric conditions. The simulation results show that this method has better forecasting ability, can provide reliable icing information in time, and ensures the flight safety under icing conditions.