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

Autor:	Ahmed Benhammou, A. Karama, Bouchra Lamrini, M-V. Le Lann
Rok vydání:	2005
Předmět:	Artificial neural network Computer science Weight decay Computer Science::Neural and Evolutionary Computation Environmental engineering Coagulation (water treatment) Water treatment Data mining Soft sensor Neural network system computer.software_genre computer
Zdroj:	Adaptive and Natural Computing Algorithms ISBN: 9783211249345
DOI:	10.1007/3-211-27389-1_23
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::48f0ed864e8adbfeed63c7e748dbd8d7 https://doi.org/10.1007/3-211-27389-1_23 Zobrazit plný text záznamu