中文摘要：

为提高GM（1,N）模型的预测精度,改进其参数估计的方法,提出基于新息优先累积法的模型。对普通累积法的累加顺序进行改进,使越新的信息的累加权重越大,越旧的信息的累加权重越小。将新息优先累积法用于GM（1,N）模型的参数估计,建立基于新息优先累积法的GM（1,N）模型。以我国水电发电量和广西农业总产值为例进行预测实验。结果表明,改进的GM（1,N）模型的预测精度明显高于基于最小二乘法的传统GM（1,N）模型,改进后的模型是一种有效的预测模型。

英文摘要：

In order to improve the prediction accuracy of GM（1,N）model,the method of parameter estimation is improved and the model based on new information priority accumulation method is proposed.This method improves the accumulation sequence of the ordinary accumulation method,and the accumulating weight of the new information is greater than the weight of the old information.New information priority accumulation method is introduced into the parameter estimation of GM（1,N）model,GM（1,N）model based on new information priority accumulation method is proposed.The simulation prediction experiment is conducted according to China＇s hydro-electricity power and the total agricultural output value of Guangxi Zhuang Autonomous Region.The result shows that the forecasting precision of the improved GM（1,N）model is apparently higher than the traditional GM（1,N）based on the least square method,and the improved model is an effective prediction model.