Abstract As forecast precision based on grey GM(1, 1) prediction model is low and lacks stability, weadvance a grey optimization model based on the least squares collocation.First, the optimal initial value of GM(1, 1) model is given by minimizingnew generation sequence prediction error in the least-squares sense. The exponential function method is used to construct new background values. Then, in order to improve grey optimization models, we build the prediction model of grey least squares collocation. Finally, by quantitative analysis,forecast analysis and comparison with other models, we determine that grey least squares collocation model is of high accuracy and stability. The model is more suitable for buildings and has certain engineering application value.
WEI Yuming,ZHANG Yongzhi. The Optimization GM(1, 1) Forecast Model and Its Application Based on Least Squares Collocation[J]. jgg, 2017, 37(3): 297-301.
WEI Yuming,ZHANG Yongzhi. The Optimization GM(1, 1) Forecast Model and Its Application Based on Least Squares Collocation[J]. jgg, 2017, 37(3): 297-301.