Title:

Comparison of MLP and RBF neural networks in the task of classifying the diameters of water pipes

Alternative title:

Porównanie sieci neuronowych MLP i RBF w zadaniu klasyfikacji średnic rur wodociągowych

Creator:

Gvishiani, Zurab ; Dawidowicz, Jacek

Subject:

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

Description:

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.

Place of publishing:

Koszalin

Publisher:

Politechnika Koszalińska

Date:

2022

Type:

artykuł w czasopiśmie

Language:

eng

Is part of:

Rocznik Ochrona Środowiska. Vol. 24, s. 505-519

Rights:

Biblioteka Politechniki Koszalińskiej

Access rights:

internet

License:

Creative Commons BY-SA 4.0