计算机科学 ›› 2015, Vol. 42 ›› Issue (6): 23-27.doi: 10.11896/j.issn.1002-137X.2015.06.005
谢晨,王睿智,李 飏,苗夺谦,焦 娜
XIE Chen, WANG Rui-zhi, LI Yang, MIAO Duo-qian and JIAO Na
摘要： 燃气涡轮机已被广泛运用于现代工业中,其跳闸事件的发生将产生巨大的经济损失,因此,对燃气涡轮机的跳闸事件进行预测有重要的经济意义。然而,燃气涡轮机跳闸的预测研究是一个崭新的领域,研究成果非常有限,且缺乏数据驱动的预测方法和理论研究。从数据的预处理开始,研究了从数据的归一化、特征选择到特征值选择、特征值粒化等系列问题,并从各个角度设计了Elman神经网络的预测模型实验,对实验结果进行对比,得到了一系列建立并改善数据驱动的Elman网络跳闸预警系统的方法和有益经验,以供其他相关研究参考。
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