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- W2390932082 abstract "PCA-GA-SVR Principle Component Analysis Cenetic Algorithm – Support Vector Regression model is constructed for that sludge recycle flow rate model of biological wastewater treatment, it is highly nonlinear. This method consists of two parts: the principal component analysis PCA and hybrid algorithm of GA-SVR supporting vector regression. First uses PCA to reduce the dimensionality. Then optimizes the SVR parameters which affecting prediction accuracy by genetic algorithm, and establishes sludge recycle processes model. Experiments show that the prediction model is effective with higher convergence speed. The prediction model has higher prediction accuracy and faster speed compared to SVR prediction model." @default.
- W2390932082 created "2016-06-24" @default.
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- W2390932082 date "2014-01-01" @default.
- W2390932082 modified "2023-09-23" @default.
- W2390932082 title "Prediction of Wastewater Sludge Recycle Volume Based On PCA-GA-SVR" @default.
- W2390932082 hasPublicationYear "2014" @default.
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