Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm
The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the i...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/15/15/2677 |
| _version_ | 1797585992603926528 |
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| author | Yihong Guan Mou Lv Shuyan Li Yanbo Su Shen Dong |
| author_facet | Yihong Guan Mou Lv Shuyan Li Yanbo Su Shen Dong |
| author_sort | Yihong Guan |
| collection | DOAJ |
| description | The optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the impact is different when a leak occurs in different nodes. In this study, sensitivity functions of different nodes were obtained according to the influence of the leakage of each node on the water distribution network. Combined with the water pressure correlation and water pressure sensitivity between nodes, the monitoring range of monitoring points and the water demand of covering nodes of monitoring points were taken as objective functions to build an optimal layout model. Taking a pipeline network in Qingdao as an example, the model was solved by using multi-objective White Whale Optimization and NSGA-II. By comparing the operation results of the four cases, it was found that the monitoring points found using multi-objective White Whale Optimization show better searching ability in terms of the sensitivity functions of different nodes. |
| first_indexed | 2024-03-11T00:15:02Z |
| format | Article |
| id | doaj.art-ebab1399f74c4307bc4832352e7f8bc6 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-11T00:15:02Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-ebab1399f74c4307bc4832352e7f8bc62023-11-18T23:46:17ZengMDPI AGWater2073-44412023-07-011515267710.3390/w15152677Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization AlgorithmYihong Guan0Mou Lv1Shuyan Li2Yanbo Su3Shen Dong4School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, ChinaZhonglian Northwest Engineering Design and Research Institute Co., Xi’an 710076, ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, ChinaSchool of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, ChinaThe optimization of sensor locations in water distribution networks has been extensively studied. Previous studies of highly sensitive nodes are usually distributed in a certain area, which leads to redundant information in the sensor network. This is because these studies do not consider that the impact is different when a leak occurs in different nodes. In this study, sensitivity functions of different nodes were obtained according to the influence of the leakage of each node on the water distribution network. Combined with the water pressure correlation and water pressure sensitivity between nodes, the monitoring range of monitoring points and the water demand of covering nodes of monitoring points were taken as objective functions to build an optimal layout model. Taking a pipeline network in Qingdao as an example, the model was solved by using multi-objective White Whale Optimization and NSGA-II. By comparing the operation results of the four cases, it was found that the monitoring points found using multi-objective White Whale Optimization show better searching ability in terms of the sensitivity functions of different nodes.https://www.mdpi.com/2073-4441/15/15/2677sensitivity functionwater supply networkoptimal sensor placementmulti-objective White Whale Optimizationmulti-objective optimization |
| spellingShingle | Yihong Guan Mou Lv Shuyan Li Yanbo Su Shen Dong Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm Water sensitivity function water supply network optimal sensor placement multi-objective White Whale Optimization multi-objective optimization |
| title | Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm |
| title_full | Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm |
| title_fullStr | Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm |
| title_full_unstemmed | Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm |
| title_short | Optimized Sensor Placement of Water Supply Network Based on Multi-Objective White Whale Optimization Algorithm |
| title_sort | optimized sensor placement of water supply network based on multi objective white whale optimization algorithm |
| topic | sensitivity function water supply network optimal sensor placement multi-objective White Whale Optimization multi-objective optimization |
| url | https://www.mdpi.com/2073-4441/15/15/2677 |
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