Abstract
The paper presents the results of artificial neural networks application to the availability indicator prediction. The forecasted results indicate that artificial networks may be used to model the reliability level of the water supply systems. The network was trained using 147 and 173 operational data from one Polish medium-sized city (distribution pipes and house connections, respectively). 50% of all data was chosen for learning, 25% for testing and 25% for validation. In prognosis phase, the best created network used 100% of 114 and 133 values for testing. Following functions were used to activate neurons in hidden and output layers: linear, logistic, hyperbolic tangent, exponential. The learning of the artificial network was performed using following input parameters: material, total length, diameter. In the optimal models hyperbolic tangent was chosen to activate the hidden and output neurons in modeling the availability indicator of house connections during 68 epochs of training. Hidden and output neurons were activated (20 epochs of learning) respectively by hyperbolic tangent and linear function during the prediction of availability indicator of distribution pipes. The maximum relative errors in learning and prognosis step were equal to 0.10% and 1.20% as well as 0.27% and 1.15% for distribution pipes and house connections, respectively.
Highlights
The suitable management of water supply systems seems to be nowadays one of the crucial aspect influencing the proper maintenance of all parts of the distribution network
As it was mentioned above, the whole data set (306 and 261 data for house connections and distribution pipes, respectively) was divided into two subsets: one used for learning the artificial network, the second to make a prediction of availability indicator using selected before one optimal Artificial neural networks (ANN) model
The results of availability indicator prediction in one Polish medium-sized city might be concluded as follows: - The generalization phenomenon of ANN allows to describe the relationships between variables without having exact knowledge about these relations. - It is needed to create the artificial network for each problem separately
Summary
The suitable management of water supply systems seems to be nowadays one of the crucial aspect influencing the proper maintenance of all parts of the distribution network. F. Ijjas [1] noticed that all problems related to water are connected with human being. The technical condition of water-pipe networks should be considered as important factor determining the way of management and maintenance of water utilities. The reliability level of water-pipe networks should be estimated very precisely and should have an influence on the water utility management. There are a lot of investigations and studies carried out in Poland and abroad concerning the failure, safety and reliability analysis of water supply system which could be treated as a part of critical buried infrastructure [2,3,4,5]
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