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The water distribution system is a spatially large and complex system. Its proper functioning is determined by having been correctly developed in its design and in the hydraulic calculations. The basic purpose of the calculations is the selection of the diameters of the water pipes and the flow of water occurring, therein. This requires careful assessment of the results obtained and accuracy in the solutions applied. Issues, centred around the control of the results of the calculations, are difficult to present, algorithmically, as they are based mainly on the experience and knowledge of the designer. The authors of the present paper decided to use RBF artificial neural networks when calculating the water flow rate in particular sections of the aforementioned water pipes. In order to solve this problem, QK1 ÷ QK7 deciding classes have been defined in order to describe problems related to the water flow rate in the pipework. The RBF neural network, based on the parameters of the water pipework, selects one of the QK1 ÷ QK7 classes; this allows the process of the evaluation of the results of the hydraulic calculations, thus obtained, to be automated, albeit only partially. Keywords—water distribution system; RBF Neural Netowrks; the water flow rate; classification

The Application of RBF Neural Networks for the Assessment of the Water Flow Rate in the Pipework