Drinking Water Treatment: a Neural Network Model for Coagulation Dosing
نویسنده
چکیده
The aim of this paper is to present the development and validation of a neural network model for on-line prediction of coagulant dosage from raw water characteristics. The main parameters influencing the coagulant dosage are firstly determined via a PCA. A brief description of the methodology used for the synthesis of neural models is given and experimental results are included. The training of the neural network is performed using the Weight Decay regularization in combination with Levenberg-Marquardt method. The simulation results of neural model compared to a linear regression model are illustrated with real data. Copyright © 2005 IFAC
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