Abstract
Based on the traditional gray GM (1, N) model, with seven kinds of gas fusion in transformer oil predicted, the actual detection times for the gas is less, the sequence accuracy is greatly reduced with an large error, and it will not conform to the standard judgment for the smooth curve. Therefore, an adaptive regression algorithm is proposed to revise each calculation result of its GM model to modify the model error. Through simulation, the sequence curves of the N data by error correction are obviously closer with a greater correlation degree. The improved gray prediction model can effectively improve the accuracy of traditional GM (1, N).
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