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中文摘要：
以灰色GM（1，1）模型初始条件的优化为主要研究目的，分别讨论了以x^（1）（1）、x^（1）（n）为初始条件的GM（1，1）建模机理；提出了同时利用x^（1）（1）和x^（1）（n）模型初始条件的新方法，以x（1）（t）的模拟值与原始数据的1-AGO序列的误差平方和最小为约束条件，推导了初始条件优化后的预测模型公式；对模型预测精度起决定性作用的参数进行分析，给出了初始条件优化后模型的适用范围。经大量的数据模拟和预测，发现初始条件优化后的GM（1，1）模型各项精度指标均优于传统的GM（1，1）模型。
英文摘要：
In order to reestablish the initial value for GM （1,1） model, we proposed a new approach to improve prediction accuracy of GM（ 1,1 ） model through optimization of the initial value, which is comprised of the first and the n-th vector as the initialization, and derived from a method of least error summation of square. Then we discussed the parameter which affects the fitting results. By contrasting the improved one to the GM （ 1,1 ） about the simulation and prediction, we can conclude that the improved one is superior in prediction and simulation, and it is proved that the optimum one widen its suitable range.
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