Hybrid neural networks as prediction models

Abstract

The paper presents hybrid neural networks as prediction models for water intake in water supply system. Previous research concerned establishing prediction models in the form of single neural networks: linear network (L), multi-layer network with error back propagation (MLP) and Radial Basis Function network (RBF). Currently, the models in the form of hybrid neural networks (L-MLP, L-RBF, MLP-RBF and L-MLP-RBF) were created. The prediction models were compared for obtaining optimal prognosis. Prediction models were done for working days, Saturdays and Sundays. The research was done for selected nodes of water supply system: detached house node and nodes for 4 hydrophore stations from different pressure areas of water supply system. Models for Sundays were presented in detail. © 2010 Springer-Verlag.