And at tile same time the methods to predict water demand hi the future, such as bp neural network, gm ( 1, 1 ) of new information with the same dimension and non-linear exponential regression, are also studied in this paper 同時,對bp神經(jīng)網(wǎng)絡(luò)、灰色gm(1,1)等維新息模型和非線性指數(shù)回歸等方法在區(qū)域需水量預(yù)測中的應(yīng)用進行了研究。
(4 ) the applications of bp neural network prediction gm ( 1, 1 ) prediction of new information with the same dimension non-linear exponential regression prediction in regional social-economic indexes are discussed in this paper (4)探討了bp神經(jīng)網(wǎng)絡(luò)預(yù)測、灰色gm(1,1)等維新息模型預(yù)測和非線性指數(shù)回歸預(yù)測等方法在區(qū)域社會經(jīng)濟指標預(yù)測中的應(yīng)用。
Fbody four kinds of forecasting models which pndchng water dernan in the lindting future are presental f cell exponential regression method . incomplete dispatch distinguish method . linear gray prediedon meil1ed i . e ., gm ( 1 . l ) and nonlinear gn pedction method 首先對未來年限的用水量進行了四種方法的預(yù)測:單元指數(shù)回歸法、殘差辨識預(yù)測法、線性灰色預(yù)測gm(1,1)法和非線性灰色預(yù)測gm(1,1,)法。