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    Leakage Detection Using Probabilistic Neural Networks and Model-Based Localization Using Quantum Genetic Algorithms in Real Water Supply Networks

    Source: Journal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002::page 04025111-1
    Author:
    Guan, Yihong
    ,
    Zhang, Wei
    ,
    Lv, Mou
    ,
    Cui, Lingzhi
    ,
    Qiao, Peng
    ,
    Zhao, Huan
    ,
    Li, Hang
    DOI: 10.1061/JPSEA2.PSENG-1944
    Publisher: American Society of Civil Engineers
    Abstract: AbstractCompanies are making significant efforts to improve leakage detection efficiency. Therefore, this paper proposes the identification of leak zones using a probabilistic neural network (PNN) and model-based localization in real water supply ...The first figure is a flowchart of the research methods in the paper, and the second figure is a comparison chart of the leak location results of the two methods. Compared with the traditional model-based localization using QGA, the accuracy of the PNN-...Practical ApplicationsThe leak detection method of water supply network based on probabilistic neural network (PNN) and quantum genetic algorithm (QGA) proposed in this paper could significantly improve the efficiency and accuracy of leak location. By ...
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      Leakage Detection Using Probabilistic Neural Networks and Model-Based Localization Using Quantum Genetic Algorithms in Real Water Supply Networks

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4313102
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    • Journal of Pipeline Systems Engineering and Practice

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    contributor authorGuan, Yihong
    contributor authorZhang, Wei
    contributor authorLv, Mou
    contributor authorCui, Lingzhi
    contributor authorQiao, Peng
    contributor authorZhao, Huan
    contributor authorLi, Hang
    date accessioned2026-08-20T12:06:16Z
    date available2026-08-20T12:06:16Z
    date copyright2025/12/23
    date issued2026
    identifier otherJPSEA2.PSENG-1944.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313102
    description abstractAbstractCompanies are making significant efforts to improve leakage detection efficiency. Therefore, this paper proposes the identification of leak zones using a probabilistic neural network (PNN) and model-based localization in real water supply ...The first figure is a flowchart of the research methods in the paper, and the second figure is a comparison chart of the leak location results of the two methods. Compared with the traditional model-based localization using QGA, the accuracy of the PNN-...Practical ApplicationsThe leak detection method of water supply network based on probabilistic neural network (PNN) and quantum genetic algorithm (QGA) proposed in this paper could significantly improve the efficiency and accuracy of leak location. By ...
    publisherAmerican Society of Civil Engineers
    titleLeakage Detection Using Probabilistic Neural Networks and Model-Based Localization Using Quantum Genetic Algorithms in Real Water Supply Networks
    typeJournal Article
    journal volume17
    journal issue2
    journal titleJournal of Pipeline Systems Engineering and Practice
    identifier doi10.1061/JPSEA2.PSENG-1944
    journal fristpage04025111-1
    journal lastpage04025111-10
    page10
    treeJournal of Pipeline Systems Engineering and Practice:;2026:;Volume ( 017 ):;issue: 002
    contenttypeFulltext
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    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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