IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v33y2019i9d10.1007_s11269-019-02296-7.html
   My bibliography  Save this article

Random Bagging Classifier and Shuffled Frog Leaping Based Optimal Sensor Placement for Leakage Detection in WDS

Author

Listed:
  • Rejeesh Rayaroth

    (Pondicherry Engineering College)

  • Sivaradje G

    (Pondicherry Engineering College)

Abstract

Water Distribution Systems (WDS) are the large scale systems that demand design of enhanced leak detection and isolation techniques to prevent from water waste. Leakages lead to imperative loss of water in water distribution networks. Many works are published on leak detection of WDS. However, the existing methods failed to improve the leakage detection accuracy and reduce the time. In this paper, Random Decision Tree Bagging Classifier based Shuffled Frog Leaping Optimization (RDTBC-SFLO) Technique is introduced. In RDTBC-SFLO, the collected pressure data are taken as training data. Random ID3 decision forest classifier process constructs the ID3 decision tree and produces the classification results of pressure data. After classification, number of nodes at abnormal pressure data is randomly generated as initial population in shuffled frog leaping optimization process. The fitness value of every node is calculated and the optimal nodes are chosen for the sensor placement in WDS with higher accuracy and minimal error rate. The simulation results show that RDTBC-SFLO technique increases the performance of water leakage detection with minimum classification time when compared to state-of-the-art works.

Suggested Citation

  • Rejeesh Rayaroth & Sivaradje G, 2019. "Random Bagging Classifier and Shuffled Frog Leaping Based Optimal Sensor Placement for Leakage Detection in WDS," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3111-3125, July.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:9:d:10.1007_s11269-019-02296-7
    DOI: 10.1007/s11269-019-02296-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-019-02296-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-019-02296-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David B. Steffelbauer & Daniela Fuchs-Hanusch, 2016. "Efficient Sensor Placement for Leak Localization Considering Uncertainties," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(14), pages 5517-5533, November.
    2. Huan-Feng Duan, 2018. "Accuracy and Sensitivity Evaluation of TFR Method for Leak Detection in Multiple-Pipeline Water Supply Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(6), pages 2147-2164, April.
    3. Marco Fagiani & Stefano Squartini & Leonardo Gabrielli & Marco Severini & Francesco Piazza, 2016. "A Statistical Framework for Automatic Leakage Detection in Smart Water and Gas Grids," Energies, MDPI, vol. 9(9), pages 1-25, August.
    4. Erfan Hajibandeh & Sara Nazif, 2018. "Pressure Zoning Approach for Leak Detection in Water Distribution Systems Based on a Multi Objective Ant Colony Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2287-2300, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guancheng Guo & Xipeng Yu & Shuming Liu & Xiyan Xu & Ziqing Ma & Xiaoting Wang & Yujun Huang & Kate Smith, 2020. "Novel Leakage Detection and Localization Method Based on Line Spectrum Pair and Cubic Interpolation Search," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(12), pages 3895-3911, September.
    2. Zukang Hu & Wenlong Chen & Beqing Chen & Debao Tan & Yu Zhang & Dingtao Shen, 2021. "Robust Hierarchical Sensor Optimization Placement Method for Leak Detection in Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(12), pages 3995-4008, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tiku T. Tanyimboh, 2017. "Informational Entropy: a Failure Tolerance and Reliability Surrogate for Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3189-3204, August.
    2. Chi Zhang & Jinzhe Gong & Martin F. Lambert & Angus R. Simpson & Aaron C. Zecchin, 2019. "Sensor Placement Strategy for Pipeline Condition Assessment Using Inverse Transient Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2761-2774, June.
    3. Andrés Ortega-Ballesteros & David Muñoz-Rodríguez & Alberto-Jesus Perea-Moreno, 2022. "Advances in Leakage Control and Energy Consumption Optimization in Drinking Water Distribution Networks," Energies, MDPI, vol. 15(15), pages 1-5, July.
    4. Caterina Capponi & Silvia Meniconi & Pedro J. Lee & Bruno Brunone & Marco Cifrodelli, 2020. "Time-domain Analysis of Laboratory Experiments on the Transient Pressure Damping in a Leaky Polymeric Pipe," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 501-514, January.
    5. Sanghyun Kim, 2019. "Valve Maneuver Prediction in Simple and Complicated Pipeline Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4671-4685, November.
    6. Dana-Mihaela Petroșanu & George Căruțașu & Nicoleta Luminița Căruțașu & Alexandru Pîrjan, 2019. "A Review of the Recent Developments in Integrating Machine Learning Models with Sensor Devices in the Smart Buildings Sector with a View to Attaining Enhanced Sensing, Energy Efficiency, and Optimal B," Energies, MDPI, vol. 12(24), pages 1-64, December.
    7. Juan Li & Wenjun Zheng & Changgang Lu, 2022. "An Accurate Leakage Localization Method for Water Supply Network Based on Deep Learning Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(7), pages 2309-2325, May.
    8. Xiang Xie & Dibo Hou & Xiaoyu Tang & Hongjian Zhang, 2019. "Leakage Identification in Water Distribution Networks with Error Tolerance Capability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(3), pages 1233-1247, February.
    9. Reza Moasheri & Mohammadreza Jalili-Ghazizadeh, 2020. "Locating of Probabilistic Leakage Areas in Water Distribution Networks by a Calibration Method Using the Imperialist Competitive Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 35-49, January.
    10. L. Berardi & O. Giustolisi, 2021. "Calibration of Design Models for Leakage Management of Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(8), pages 2537-2551, June.
    11. Sara Azargashb Lord & Seied Mehdy Hashemy Shahdany & Abbas Roozbahani, 2021. "Minimization of Operational and Seepage Losses in Agricultural Water Distribution Systems Using the Ant Colony Optimization," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(3), pages 827-846, February.
    12. Sang Hyun Kim, 2023. "Generalized Impedance-based Transient Analysis for Multi-branched Pipeline Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1581-1597, March.
    13. Chi Zhang & Martin F. Lambert & Jinzhe Gong & Aaron C. Zecchin & Angus R. Simpson & Mark L. Stephens, 2020. "Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2807-2820, July.
    14. Chan-Wook Lee & Do-Guen Yoo, 2021. "Development of Leakage Detection Model and Its Application for Water Distribution Networks Using RNN-LSTM," Sustainability, MDPI, vol. 13(16), pages 1-15, August.
    15. Juan Li & Ying Wu & Wenjun Zheng & Changgang Lu, 2021. "A Model-Based Bayesian Framework for Pipeline Leakage Enumeration and Location Estimation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(13), pages 4381-4397, October.
    16. Najam us Saqib & Muhammad Faizan Mysorewala & Lahouari Cheded, 2017. "A Multiscale Approach to Leak Detection and Localization in Water Pipeline Network," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3829-3842, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:33:y:2019:i:9:d:10.1007_s11269-019-02296-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.