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 and Technology|
|Deposited By:||Professor Bogdan Gabrys|
|Deposited On:||11 Mar 2009 21:48|
|Last Modified:||10 Sep 2014 14:44|
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