草原与草坪
草原與草坪
초원여초평
GRASSLAND AND TURF
2014年
2期
23-27
,共5页
人工神经网络%甘肃省%≥0 ℃年积温%空间插值
人工神經網絡%甘肅省%≥0 ℃年積溫%空間插值
인공신경망락%감숙성%≥0 ℃년적온%공간삽치
artificial neural network%Gansu Province%annual accumulative temperature%spatial interpolation
中国西部地区气象站点空间分布不均匀,而且数量较少,导致气象要素空间插值的误差较大。以甘肃省为研究区,将其划分为东、中、西3个插值区域,利用人工神经网络方法,对1960~2009年气象站点地面观测的≥0℃年积温值进行拟合,将202个气象站点数据扩展到586个,插值结果表明:3个区域年积温平均绝对误差(MAE)为246.53℃、平均相对误差(MRE)为8.37%;东中西3个区域精度与原有气象站点数据量有明显关系。研究方法和结果可为进行甘肃省生态环境变化研究提供方法和数据参考,为进一步进行区域空间插值提供数据基础。
中國西部地區氣象站點空間分佈不均勻,而且數量較少,導緻氣象要素空間插值的誤差較大。以甘肅省為研究區,將其劃分為東、中、西3箇插值區域,利用人工神經網絡方法,對1960~2009年氣象站點地麵觀測的≥0℃年積溫值進行擬閤,將202箇氣象站點數據擴展到586箇,插值結果錶明:3箇區域年積溫平均絕對誤差(MAE)為246.53℃、平均相對誤差(MRE)為8.37%;東中西3箇區域精度與原有氣象站點數據量有明顯關繫。研究方法和結果可為進行甘肅省生態環境變化研究提供方法和數據參攷,為進一步進行區域空間插值提供數據基礎。
중국서부지구기상참점공간분포불균균,이차수량교소,도치기상요소공간삽치적오차교대。이감숙성위연구구,장기화분위동、중、서3개삽치구역,이용인공신경망락방법,대1960~2009년기상참점지면관측적≥0℃년적온치진행의합,장202개기상참점수거확전도586개,삽치결과표명:3개구역년적온평균절대오차(MAE)위246.53℃、평균상대오차(MRE)위8.37%;동중서3개구역정도여원유기상참점수거량유명현관계。연구방법화결과가위진행감숙성생태배경변화연구제공방법화수거삼고,위진일보진행구역공간삽치제공수거기출。
There are uneven distribution of a few meteorological stations in western China,which result in more errors in spatial interpolation of meteorological elements.Selected Gansu as study area,dividing into east-ern,middle and western region,the paper used artificial neural network to fit ≥0 ℃ annual accumulative tem-perature between 1 960 ~ 2009 and extended the meteorological data from 202 meteorological stations to 586 sites.The results of the interpolation showed that the mean absolute error (MAE)and mean relative error (MRE)of average annual accumulative temperature in three regions were 246.53 ℃ and 8.37%,respectively. The accuracy of data is related to the number of meteorological stations.The study provide the approach and references for the study of ecological environment in Gansu,and the basis for further studying of regional spatial interpolation.