期刊
SYMMETRY-BASEL
卷 13, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/sym13081518
关键词
machine learning; prediction; classification algorithms; water pump failure; optimization
资金
- Serbian Ministry of Education, Science and Technological Development through the Mathematical Institute of the Serbian Academy of Sciences and Arts
The paper aims to develop a model to predict water pump failure using machine learning algorithms, improving the efficiency and management of wastewater treatment systems. By using classification algorithms, future values can be predicted based on current values, along with probabilities of each sample belonging to each class.
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.
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