The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
以东北地区为研究对象,分析多年冻土退化程度及空间分布。通过收集关键气象要素,使用多元线性回归模型修正部分地面温度,基于多年冻土顶部温度(temperature at the top of permafrost,TTOP)模型,利用ANUSPILN软件进行插值,分析东北多年...以东北地区为研究对象,分析多年冻土退化程度及空间分布。通过收集关键气象要素,使用多元线性回归模型修正部分地面温度,基于多年冻土顶部温度(temperature at the top of permafrost,TTOP)模型,利用ANUSPILN软件进行插值,分析东北多年冻土时空分布变化。结果表明,1970 s、1980 s、1990 s、2000 s、2010 s的多年冻土面积分别约为3.99×10^(5)、3.41×10^(5)、2.31×10^(5)、1.80×10^(5)、1.59×10^(5) km^(2)。1970 s—2010 s,东北地区的多年冻土面积显著减少约2.40×10^(5) km^(2),降幅高达60.08%。多年冻土面积占东北地区总面积的比例从27.66%下降至11.04%,而季节性冻土面积比例则从72.34%增加至88.96%。模型结果与实际钻孔数据差值仅为0.05℃,且使用修正地面温度数据的模型结果高于现有研究结果。展开更多
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
文摘以东北地区为研究对象,分析多年冻土退化程度及空间分布。通过收集关键气象要素,使用多元线性回归模型修正部分地面温度,基于多年冻土顶部温度(temperature at the top of permafrost,TTOP)模型,利用ANUSPILN软件进行插值,分析东北多年冻土时空分布变化。结果表明,1970 s、1980 s、1990 s、2000 s、2010 s的多年冻土面积分别约为3.99×10^(5)、3.41×10^(5)、2.31×10^(5)、1.80×10^(5)、1.59×10^(5) km^(2)。1970 s—2010 s,东北地区的多年冻土面积显著减少约2.40×10^(5) km^(2),降幅高达60.08%。多年冻土面积占东北地区总面积的比例从27.66%下降至11.04%,而季节性冻土面积比例则从72.34%增加至88.96%。模型结果与实际钻孔数据差值仅为0.05℃,且使用修正地面温度数据的模型结果高于现有研究结果。
