Abstract
In order to solve the influence of different original data series on model adaptability and fitting accuracy in non-equidistant grey model. Because the background value in the gray model is a key factor affecting the accuracy and adaptability of the model. Faced with this situation, this article uses the Newton-Cotes quadrature formula to optimize the background value, which improves the adaptability and fitting accuracy of the non-equidistant gray model. By constructing the model, the Newton-Cotes quadrature formula is applied to the application of the non-equidistant GM (1,1) modeling method in the settlement and deformation of buildings. The analysis shows that the new model method prediction is more suitable for building settlement monitoring and analysis, and the degree of fit is improved by about 30%. The new model is better than the traditional model.
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