Application of improved GM (1, m) model for transformer faults prediction. Issue 5 (August 2020) - Chen, Guoping; Shi, Yujie; She, Haizhi; Qin, Yanjun; Zhou, Xiaohong; Qi, Zhengdong; Guo, Wenke
Abstract: The traditional GM (1, m) prediction model is improved, the original data sequence is transformed, and its data generation method is changed, so that the transformed data sequence has a more approximate exponential change property, which meets the gray model's smoothness Requirements, to be able to predict fluctuation series. At the same time, in order to improve the prediction accuracy of the model, the model background value is optimized, so that the prediction accuracy of the model is greatly improved. The improved GM (1, 7) prediction model is used to predict the volume fraction of various gas characteristics of the transformer. Compared with the traditional GM (1, 1) and GM (1, 7) prediction results, it has a good approximation to the original data sequence the effect shows the effectiveness of the model.