Application of Systematical Optimization GM(1,1) Model Based on Lifting Wavelet in Dam Displacement Forecast

Abstract:

A new GM(1,1) model is proposed in the paper thinking about of the influence of the traditional modeling accuracy bias of subjective modeling and noise interfere. Using the new model, the noisy part of monitoring data could be deleted and prediction error could be decreased. At the same time, the constraint conditions of minimum fitting error sum of squares of each variable during once accumulation is raised to build and optimize a prediction model with optimal initial values based on the Principle of Least Squares. Moreover, the new GM(1,1) model is established by improving the background value and gray value with consideration of systematical optimization. Finally through the practical case, the results show that the calculation result of using the new GM(1,1) model is smaller and the accuracy is higher than using the traditional model.

• Periodical: Applied Mechanics and Materials (Volumes 488-489)
• Pages: 759-764
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.488-489.759
• Online since: January 2014
• Authors: Ke Hong Zheng*, Zhi Qiang Wang
• Keywords: Dam Displacement, Lifting Wavelet, Systematical Optimization

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DOI: 10.1016/s1874-8651(10)60040-3

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