Neural Simulation of Water Systems for Efficient State Estimation.

Gabrys, B. and Bargiela, A., 1995. Neural Simulation of Water Systems for Efficient State Estimation. In: The European Simulation and Modelling Conference (ESM'95), June 5-7, 1995, Prague, Czech Republic, pp. 775-779.

Full text available as:

Gabrys_Bargiela_ESM95.pdf - Published Version



This paper presents a neural network based technique for the solution of a water system state estimation problem.The technique combines a neural linear equations solver with a Newton-Raphson iterations to obtain a solution to an overdetermined set of nonlinear equations. The algorithm has been applied to a realistic 34-node water network. By changing the values of neural network parameters both the least squares (LS) and least absolute values (LAV) estimates have been obtained and assessed with respect to their sensitivity to measurement errors.

Item Type:Conference or Workshop Item (Paper)
Subjects:Generalities > Computer Science and Informatics > Artificial Intelligence
Generalities > Computer Science and Informatics
Technology > Engineering > General Engineering
Group:Faculty of Science & Technology
ID Code:9643
Deposited By: Professor Bogdan Gabrys
Deposited On:11 Mar 2009 21:48
Last Modified:10 Sep 2014 14:44


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