{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T14:11:25Z","timestamp":1775225485350,"version":"3.50.1"},"reference-count":32,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>One way to optimize wastewater treatment system infrastructure, its operations, monitoring, maintenance and management is through development of smart forecasting, monitoring and failure prediction systems using machine learning modeling. The aim of this paper was to develop a model that was able to predict a water pump failure based on the asymmetrical type of data obtained from sensors such as water levels, capacity, current and flow values. Several machine learning classification algorithms were used for predicting water pump failure. Using the classification algorithms, it was possible to make predictions of future values with a simple input of current values, as well as predicting probabilities of each sample belonging to each class. In order to build a prediction model, an asymmetrical type dataset containing the aforementioned variables was used.<\/jats:p>","DOI":"10.3390\/sym13081518","type":"journal-article","created":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T22:51:00Z","timestamp":1629327060000},"page":"1518","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Wastewater Plant Reliability Prediction Using the Machine Learning Classification Algorithms"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8737-1928","authenticated-orcid":false,"given":"Lazar Z.","family":"Velimirovi\u0107","sequence":"first","affiliation":[{"name":"Mathematical Institute of the Serbian Academy of Sciences and Arts, Kneza Mihaila 36, 11001 Belgrade, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3424-134X","authenticated-orcid":false,"given":"Radmila","family":"Jankovi\u0107","sequence":"additional","affiliation":[{"name":"Mathematical Institute of the Serbian Academy of Sciences and Arts, Kneza Mihaila 36, 11001 Belgrade, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3745-3033","authenticated-orcid":false,"given":"Jelena D.","family":"Velimirovi\u0107","sequence":"additional","affiliation":[{"name":"Mathematical Institute of the Serbian Academy of Sciences and Arts, Kneza Mihaila 36, 11001 Belgrade, Serbia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8677-5162","authenticated-orcid":false,"given":"Aleksandar","family":"Janji\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Electronic Engineering, University of Nis, Aleksandra Medvedeva 14, 18000 Nis, Serbia"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1109\/MCS.2006.1657877","article-title":"Control issues and challenges in waste water treatment plants","volume":"26","author":"Hamitlon","year":"2006","journal-title":"IEEE Control Syst. 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