Abstract: Unascertained filtering and grey model are applied to predict dam deformation as the prediction accuracy is inevitably influenced by the gross error of observation sequence on the one hand and the short observation sequence itself on the other. The gross error of dam deformation observation sequence is detected and corrected by unascertained filtering method, and subsequently the grey model is employed to predict the dam deformation. The integration of the two processes is proved by case study to be of high practical value with remarkably improved prediction accuracy.

Key words: unascertained filtering method ,    grey model  ,   dam deformation  ,   prediction