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The paper presents possibilities of application of selected regression methods (classification trees, support vector machines, K-nearest neighbours, artificial networks) for classification of sewers’ damages. Operational data from the time span 2006–2011 obtained from water utility were used for deterioration analysis. On the basis of the following independent variables, the modelling was carried out: diameter, depth, year of construction, material and season of damage’s occurring. The following kinds of damages were classified: corrosion, crack, longitudinal crack, displacement, unsealing, failure, collapse. The main aim of the paper was to check if prediction methodology could be useful for classification of different kinds of sewers’ damages. The obtained results pointed out that proposed classification methods are not appropriable in quality analysis of registered damages of sewers. Moreover, it is recommended for water and sewerage companies to register types of failures using unified notation which make easier preliminary classification before applying modelling approach. The calculations were performed in Statistica 13.1 software.
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