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Hybrid Neural Networks as Prediction Models

  • Izabela Rojek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6114)

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.

Keywords

prediction model hybrid neural network water supply system 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Izabela Rojek
    • 1
  1. 1.Institute of Mechanics and Applied Computer ScienceKazimierz Wielki University in BydgoszczBydgoszczPoland

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