针对微波加热制备部分稳定氧化锆过程的非线性、多变量、时变等复杂特点,运用机器学习方法中的LM-BP神经网络和支持向量机(SVM),以保温温度、升温速率、保温时间、降温速率和淬火温度作为输入量,稳定率为输出值,建立了微波加热制备部分稳定氧化锆的稳定率预测模型.分别利用两种预测模型进行稳定率的预测,通过与稳定率的测量值对比分析表明,两者均具有良好的预测能力,但SVM模型具有较高的预测精度.
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