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- W2351155625 abstract "A method combined principal component analysis and BP artificial neural network for coalbed methane(CBM)wells to predict productivity has been proposed in the paper,which has better simulation and prediction functions.The average relative error between the factual data and predicted data is 1.67%,the max 3.33% and the min 0.22%,showing high precision as well as presenting a means to predict productivity for CBM using production parameters.The approach of BP artificial neural network for CBM wells to predict productivity brings in principal component analysis so that the operating efficiency can be increased validly.As for certain CBM wells without obvious production rules,the method could obtain nonlinear mapping relation,realizing production prediction." @default.
- W2351155625 created "2016-06-24" @default.
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- W2351155625 date "2013-01-01" @default.
- W2351155625 modified "2023-09-23" @default.
- W2351155625 title "A Method Combined Principal Component Analysis and BP Artificial Neural Network for Coalbed Methane(CBM)Wells to Predict Productivity" @default.
- W2351155625 hasPublicationYear "2013" @default.
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