A neural network system for modelling of coagulant dosage used in drinking water treatment

摘要

This paper presents the elaboration and validation of "soft sensor" using neural networks for on-line estimation of the coagulation dose 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 model 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 performance of this soft sensor is illustrated with real data.