Rahi, Majid, Ebrahimnejad, Ali, Motameni, Homayun. (1404). The application of machine learning algorithms with a fuzzy approach to investigating faults in the control system of consumable water resources. هنرهای کاربردی, 16(9), 107-116. doi: 10.22075/ijnaa.2024.33191.4941
Majid Rahi; Ali Ebrahimnejad; Homayun Motameni. "The application of machine learning algorithms with a fuzzy approach to investigating faults in the control system of consumable water resources". هنرهای کاربردی, 16, 9, 1404, 107-116. doi: 10.22075/ijnaa.2024.33191.4941
Rahi, Majid, Ebrahimnejad, Ali, Motameni, Homayun. (1404). 'The application of machine learning algorithms with a fuzzy approach to investigating faults in the control system of consumable water resources', هنرهای کاربردی, 16(9), pp. 107-116. doi: 10.22075/ijnaa.2024.33191.4941
Rahi, Majid, Ebrahimnejad, Ali, Motameni, Homayun. The application of machine learning algorithms with a fuzzy approach to investigating faults in the control system of consumable water resources. هنرهای کاربردی, 1404; 16(9): 107-116. doi: 10.22075/ijnaa.2024.33191.4941

The application of machine learning algorithms with a fuzzy approach to investigating faults in the control system of consumable water resources

International Journal of Nonlinear Analysis and Applications
مقاله 10، دوره 16، شماره 9، آذر 2025، صفحه 107-116    اصل مقاله (1.39 M)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2024.33191.4941
نویسندگان
Majid Rahi1؛ Ali Ebrahimnejad* 2؛ Homayun Motameni3
1Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran
2Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
3Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
چکیده
Nowadays, proper management of water resources is essential due to the scarcity of freshwater resources and the high cost of wastewater treatment. To control and optimize while avoiding human mistakes, it is necessary to design and implement an intelligent automated system to minimize human intervention. On the other hand, inevitable deficiencies in system equipment require fault detection and localization methods, all of which involve time and cost. Nevertheless, these costs can be reduced by examining faults in the design phase before entering the implementation phase. This article uses a simulated sample system to demonstrate the method's effectiveness. In this way, system faults in the design phase are predicted through machine learning methods. The system's tolerance for dealing with them is evaluated using fuzzy approaches. The proposed approach consists of a process-oriented framework comprising offline and online phases.
کلیدواژه‌ها
Fault Tolerance؛ Decision Tree؛ Fuzzy Sets؛ Water Resources Management System
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