Comparison of MLP and RBF Neural Networks in the Task of Classifying the Diameters of Water Pipes

Rocznik Ochrona Środowiska 2022, vol. 24, pp. 505-519

Zurab Gvishiani¹ ,Jacek Dawidowicz² This email address is being protected from spambots. You need JavaScript enabled to view it.

	1. Georgian Technical University, Faculty of Civil Engineering, Georgia 2. Bialystok University of Technology, Poland
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	https://doi.org/10.54740/ros.2022.036

Hydraulic calculations of water distribution systems are currently performed using computer programs. In addition to the basic calculation procedure, modules responsible for evaluating the obtained calculation results are introduced more and more often into the programs. This article presents the results of research on artificial neural networks with a radial base function (RBF) and a multilayer perceptron (MLP), aimed at determining whether they can be used to model the relationship between the variables describing the computational section of the water distribution system and the diameter of the water pipe. The classification capabilities of the RBF and MLP networks were analyzed according to the number of neurons in the hidden layer of the network. A comparative analysis of RBF networks with multilayer perceptron (MLP) networks was performed. The results showed that the MLP networks have much better classification properties and are better suited for the task of assessing the selected diameters of the water pipes.

water distribution system, hydraulic calculations, selection of diameters of water pipes, artificial neural networks, radial basis function, multilayer perceptron

AMA Style
Gvishiani Z, Dawidowicz J. Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes. Rocznik Ochrona Środowiska. 2022; 24. https://doi.org/10.54740/ros.2022.036

ACM Style
Gvishiani, Z., Dawidowicz, J. 2022. Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes. Rocznik Ochrona Środowiska. 24. DOI:https://doi.org/10.54740/ros.2022.036

ACS Style
Gvishiani, Z.; Dawidowicz, J. Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes Rocznik Ochrona Środowiska 2022, 24, 505-519. https://doi.org/10.54740/ros.2022.036

APA Style
Gvishiani, Z., Dawidowicz, J. (2022). Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes. Rocznik Ochrona Środowiska, 24, 505-519. https://doi.org/10.54740/ros.2022.036

ABNT Style
GVISHIANI, Z.; DAWIDOWICZ, J. Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes. Rocznik Ochrona Środowiska, v. 24, p. 505-519, 2022. https://doi.org/10.54740/ros.2022.036

Chicago Style
Gvishiani, Zurab, Dawidowicz, Jacek. 2022. "Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes". Rocznik Ochrona Środowiska 24, 505-519. https://doi.org/10.54740/ros.2022.036

Harvard Style
Gvishiani, Z., Dawidowicz, J. (2022) "Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes", Rocznik Ochrona Środowiska, 24, pp. 505-519. doi:https://doi.org/10.54740/ros.2022.036

IEEE Style
Z. Gvishiani, J. Dawidowicz, "Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes", RoczOchrSrod, vol 24, pp. 505-519. https://doi.org/10.54740/ros.2022.036