Enhancing water pump failure prediction using machine learning: a focus on less-explored variables
In recent years, there has been a surge in research exploring the potential of Machine Learning (ML) for predicting water pump failures. While some studies have focused on supervised approaches, others have delved into unsupervised methods. However, the challenge lies in identifying the key variable...
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| Format: | Article |
| Language: | English |
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REA Press
2023-09-01
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| Series: | Computational Algorithms and Numerical Dimensions |
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| Online Access: | https://www.journal-cand.com/article_188454_427f94bfa1f3de8eb7566b2abeff636b.pdf |
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| author | Reza Rasinojehdehi Goran Cirovic |
| author_facet | Reza Rasinojehdehi Goran Cirovic |
| author_sort | Reza Rasinojehdehi |
| collection | DOAJ |
| description | In recent years, there has been a surge in research exploring the potential of Machine Learning (ML) for predicting water pump failures. While some studies have focused on supervised approaches, others have delved into unsupervised methods. However, the challenge lies in identifying the key variables crucial for accurate failure predictions. This study bridges this gap by consulting domain experts to discern essential variables, including water catchment area level, water quality index, lubrication frequency, water reservoir temperature, operating time, and power interruptions count. Employing supervised ML methods, specifically multiple regression and decision tree cart, the research aims to enhance the precision of failure predictions, shedding light on less-explored variables that play a significant role in pump failure. |
| format | Article |
| id | doaj-art-f4e158cc227a4ae89da6798ce6208ef7 |
| institution | Kabale University |
| issn | 2980-7646 2980-9320 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | REA Press |
| record_format | Article |
| series | Computational Algorithms and Numerical Dimensions |
| spelling | doaj-art-f4e158cc227a4ae89da6798ce6208ef72025-01-30T11:22:16ZengREA PressComputational Algorithms and Numerical Dimensions2980-76462980-93202023-09-012312413510.22105/cand.2024.437591.1088188454Enhancing water pump failure prediction using machine learning: a focus on less-explored variablesReza Rasinojehdehi0Goran Cirovic1Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.Faculty of Technical Sciences, University of Novi Sad, Trg Dositeja Obradovica-6, 21000 Novi Sad, Serbia.In recent years, there has been a surge in research exploring the potential of Machine Learning (ML) for predicting water pump failures. While some studies have focused on supervised approaches, others have delved into unsupervised methods. However, the challenge lies in identifying the key variables crucial for accurate failure predictions. This study bridges this gap by consulting domain experts to discern essential variables, including water catchment area level, water quality index, lubrication frequency, water reservoir temperature, operating time, and power interruptions count. Employing supervised ML methods, specifically multiple regression and decision tree cart, the research aims to enhance the precision of failure predictions, shedding light on less-explored variables that play a significant role in pump failure.https://www.journal-cand.com/article_188454_427f94bfa1f3de8eb7566b2abeff636b.pdfmachine learningwater pump failure predictionmulti-variable regressiondecision tree cart |
| spellingShingle | Reza Rasinojehdehi Goran Cirovic Enhancing water pump failure prediction using machine learning: a focus on less-explored variables Computational Algorithms and Numerical Dimensions machine learning water pump failure prediction multi-variable regression decision tree cart |
| title | Enhancing water pump failure prediction using machine learning: a focus on less-explored variables |
| title_full | Enhancing water pump failure prediction using machine learning: a focus on less-explored variables |
| title_fullStr | Enhancing water pump failure prediction using machine learning: a focus on less-explored variables |
| title_full_unstemmed | Enhancing water pump failure prediction using machine learning: a focus on less-explored variables |
| title_short | Enhancing water pump failure prediction using machine learning: a focus on less-explored variables |
| title_sort | enhancing water pump failure prediction using machine learning a focus on less explored variables |
| topic | machine learning water pump failure prediction multi-variable regression decision tree cart |
| url | https://www.journal-cand.com/article_188454_427f94bfa1f3de8eb7566b2abeff636b.pdf |
| work_keys_str_mv | AT rezarasinojehdehi enhancingwaterpumpfailurepredictionusingmachinelearningafocusonlessexploredvariables AT gorancirovic enhancingwaterpumpfailurepredictionusingmachinelearningafocusonlessexploredvariables |