Leakage detection in water distribution networks using machine-learning strategies
| العنوان: | Leakage detection in water distribution networks using machine-learning strategies |
|---|---|
| المؤلفون: | Sousa, Diego Perdigão, Du, Rong, Barros da Silva Junior, Jose Mairton, Ph.D., Cavalcante, Charles Casimiro, Fischione, Carlo |
| المصدر: | Water Science and Technology. 23(3):1115-1126 |
| مصطلحات موضوعية: | clustering, leakage detection, supervised learning, unsupervised learning, water distribution network, Machine learning, Maskininlärning |
| الوصف: | This work proposes a reliable leakage detection methodology for water distribution networks (WDNs) using machine-learning strategies. Our solution aims at detecting leakage in WDNs using efficient machine-learning strategies. We analyze pressure measurements from pumps in district metered areas (DMAs) in Stockholm, Sweden, where we consider a residential DMA of the water distribution network. Our proposed methodology uses learning strategies from unsupervised learning (K-means and cluster validation techniques), and supervised learning (learning vector quantization algorithms). The learning strategies we propose have low complexity, and the numerical experiments show the potential of using machine-learning strategies in leakage detection for monitored WDNs. Specifically, our experiments show that the proposed learning strategies are able to obtain correct classification rates up to 93.98%. |
| وصف الملف: | |
| URL الوصول: | https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-509708 https://doi.org/10.2166/ws.2023.054 |
| قاعدة البيانات: | SwePub |
| تدمد: | 16069749 16070798 |
|---|---|
| DOI: | 10.2166/ws.2023.054 |