亚博app

基于5种人工智能模型计算重庆地区参考作物蒸散量
1, 1, 1, 2

(1.zhongqingshishuilidianlijianzhukanceshejiyanjiuyuan, zhongqing 400020; 2.xinandaxue ziyuanhuanjingxueyuan, zhongqing 400715)

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Calculation of Reference Crop Evapotranspiration in Chongqing Based on 5 Artificial Intelligent Models
BAO Lingling1, YANG Yonggang1, LIU Jianjun1, ZHANG Weihua2

亚博app (1.chongqing surveying and design institute of water resources, electric power and architecture, chongqing 400020, china; 2.college of resources and environment, southwest university, chongqing 400715, china)

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备注

亚博appweihuodejisuanzhongqingdiqucankaozuowuzhengsanliang(reference crop evapotranspiration,et0)dezuiyoumoxing,xuanyongzhichixiangliangjimoxing(svm)、gaosizhishumoxing(gem)、suijisenlinmoxing(rf)、jixianxuexijimoxing(elm)heguangyihuiguishenjingwangluomoxing(grnn)5zhongrengongzhinengmoxing,yifengdou、fengjie、shapingba、wanzhou、youyanggong5gezhandian1991—2016niandezhuriqixiangshujuweijichu,gusuanet0rizhi、yuezhi,bingyupenman-monteith(p-m)jisuanjieguojinxingleduibi,jieguobiaoming:butongmoxingjingducunzaichayi,zaixiangtongqixiangcanshushurudeqingkuangxia,rengongzhinengmoxingjisuanjingduyaogaoyujingyanmoxing,zaixiangtongcanshushurudeqingkuangxia,gemmoxingwuchazhibiaozuidieryizhixingzhibiaozuigao,rizhaoshishunshiyingxiangzhongqingdiquet0bianhuaheyingxiangmoxingjingdudezuiguanjianyinsu,ergemmoxingweizhongqingdiquet0gusuandezuiyourengongzhinengmoxing。

in order to obtain the optimal model for calculating reference crop evapotranspiration(et0)in chongqing, the five artificial intelligent models such as support vector machines(svm), gaussian exponential model(gem), random forest model(rf), extreme learning machine model(elm)and generalized regression neural network model(grnn)were used as the calculation models. based on the daily meteorological data from fengdu, fengjie, shapingba, wanzhou, and youyang from 1991 to 2016, the daily and monthly et0 under different combinations of meteorological parameter inputs were estimated, and compared with the calculation results of the standard model penman-monteith(pm). the results show that the accuracies of different models are different; under the input of the same meteorological parameters, the calculation accuracy of the artificial intelligence model is higher than that of the empirical model; the error index of the gem model is the lowest and the consistency index is the highest. sunshine duration is the most critical factor impacting the accuracy of modeling and change in et0 in chongqing. gem model is the optimal artificial intelligence model to estimate et0 in chongqing.

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