基于灰色马尔可夫模型的柴油机磨损趋势预测

The Forecast for the Wear Trend of the Diesel Engine Based on Grey Markov Chain Model

在柴油机磨损趋势灰色预测的基础上,引入马尔可夫链预测理论,建立柴油机磨损趋势灰色马尔可夫预测模型。该模型既考虑了从时间序列中挖掘数据的演变规律,又通过状态转移概率矩阵的变换提取数据的随机响应,因而可将时间序列数据固有的2种性质有机结合起来,具有严密的科学性,从而拓宽了灰色预测的应用范围。实例计算证明:柴油机磨损趋势灰色马尔可夫预测模型预测精度高于GM(1,1)模型预测精度。

Based on grey method of the forecast for wear trend of the diesel engine, the Markov chains prediction method was presented and the grey Markov model for predicting the trend of the diesel engine was built. The model is felled together two kinds of inherent quality that is evolvement rules is mined from time list data and random response is attained through state transfer probability matrix organically, which make it more scientific and rigorous. So it opens up appliance scope of grey prediction. The example shows that the precision of grey Markov for predicting the trend is better than that of grey model.