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中文摘要：
针对灰色GM（1,1）预测模型预测结果精度低、模型缺乏稳定性的问题,基于最小二乘配置理论的GM（1,1）预测优化模型,首先通过使得生成序列新预测值的误差在最小二乘意义下最小,选取GM（1,1）模型的最优初值,利用指数函数法构造新的背景值;然后将优化的GM（1,1）模型和最小二乘配置理论有机结合,进一步对优化的GM（1,1）模型进行改进,构建优化的灰色最小二乘配置预测模型;最后通过对建筑物的沉降数据进行定量分析与预报,与其他模型进行对比分析。
英文摘要：
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 col- location. Finally, by quantitative analysis, forecast analysis and comparison with other models, we de- termine 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.
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