IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v30y2016i8d10.1007_s11269-016-1321-y.html
   My bibliography  Save this article

Parameter Identification of Nonlinear Muskingum Model with Backtracking Search Algorithm

Author

Listed:
  • Xiaohui Yuan

    (Huazhong University of Science and Technology)

  • Xiaotao Wu

    (Huazhong University of Science and Technology)

  • Hao Tian

    (Huazhong University of Science and Technology)

  • Yanbin Yuan

    (Wuhan University of Technology)

  • Rana Muhammad Adnan

    (Huazhong University of Science and Technology)

Abstract

Nonlinear Muskingum model is a popular approach widely used for flood routing in hydraulic engineering. An improved backtracking search algorithm (BSA) is proposed to estimate the parameters of nonlinear Muskingum model. The orthogonal designed initialization population strategy and chaotic sequences are introduced to improve the exploration and exploitation ability of BSA. At the same time, a selection strategy based individual feasibility violation is developed to ensure that the computed outflows are non-negative in the evolutionary process. Finally, three examples are employed to demonstrate the performance of the improved BSA. The comparison between the results of routing outflows and those of Wilcoxon signed ranks test shows that the improved BSA outperforms particle swarm optimization, genetic algorithm, differential evolution and other algorithms reported in the literature in terms of solution quality. Therefore, it is reasonable to draw the conclusion that the proposed BSA is a satisfactory and efficient choice for parameter estimation of nonlinear Muskingum model.

Suggested Citation

  • Xiaohui Yuan & Xiaotao Wu & Hao Tian & Yanbin Yuan & Rana Muhammad Adnan, 2016. "Parameter Identification of Nonlinear Muskingum Model with Backtracking Search Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(8), pages 2767-2783, June.
    • Handle: RePEc:spr:waterr:v:30:y:2016:i:8:d:10.1007_s11269-016-1321-y
    DOI: 10.1007/s11269-016-1321-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-016-1321-y
    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/s11269-016-1321-y?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. Zaw Latt, 2015. "Application of Feedforward Artificial Neural Network in Muskingum Flood Routing: a Black-Box Forecasting Approach for a Natural River System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 4995-5014, November.
    2. Omid Bozorg Haddad & Farzan Hamedi & Hosein Orouji & Maryam Pazoki & Hugo Loáiciga, 2015. "A Re-Parameterized and Improved Nonlinear Muskingum Model for Flood Routing," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(9), pages 3419-3440, July.
    3. Gong, Wenyin & Cai, Zhihua, 2009. "An improved multiobjective differential evolution based on Pareto-adaptive [epsilon]-dominance and orthogonal design," European Journal of Operational Research, Elsevier, vol. 198(2), pages 576-601, October.
    4. Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
    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. Chen, Zhihuan & Yuan, Xiaohui & Yuan, Yanbin & Lei, Xiaohui & Zhang, Binqiao, 2019. "Parameter estimation of fuzzy sliding mode controller for hydraulic turbine regulating system based on HICA algorithm," Renewable Energy, Elsevier, vol. 133(C), pages 551-565.
    2. Majid Niazkar & Seied Hosein Afzali, 2016. "Application of New Hybrid Optimization Technique for Parameter Estimation of New Improved Version of Muskingum Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4713-4730, October.
    3. Wen-chuan Wang & Wei-can Tian & Dong-mei Xu & Kwok-wing Chau & Qiang Ma & Chang-jun Liu, 2023. "Muskingum Models’ Development and their Parameter Estimation: A State-of-the-art Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3129-3150, June.
    4. Dariusz Gąsiorowski & Romuald Szymkiewicz, 2020. "Identification of Parameters Influencing the Accuracy of the Solution of the Nonlinear Muskingum Equation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3147-3164, August.
    5. Reyhaneh Akbari & Masoud-Reza Hessami-Kermani & Saeed Shojaee, 2020. "Flood Routing: Improving Outflow Using a New Non-linear Muskingum Model with Four Variable Parameters Coupled with PSO-GA Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3291-3316, August.
    6. Hassan, Bryar A. & Rashid, Tarik A., 2020. "Operational framework for recent advances in backtracking search optimisation algorithm: A systematic review and performance evaluation," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    7. Jalal Bazargan & Hadi Norouzi, 2018. "Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4763-4777, November.
    8. Ling Kang & Liwei Zhou & Song Zhang, 2017. "Parameter Estimation of Two Improved Nonlinear Muskingum Models Considering the Lateral Flow Using a Hybrid Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(14), pages 4449-4467, November.
    9. Aryan Salvati & Alireza Moghaddam Nia & Ali Salajegheh & Parham Moradi & Yazdan Batmani & Shahabeddin Najafi & Ataollah Shirzadi & Himan Shahabi & Akbar Sheikh-Akbari & Changhyun Jun & John J. Clague, 2023. "Performance improvement of the linear muskingum flood routing model using optimization algorithms and data assimilation approaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(3), pages 2657-2690, 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. Jalal Bazargan & Hadi Norouzi, 2018. "Investigation the Effect of Using Variable Values for the Parameters of the Linear Muskingum Method Using the Particle Swarm Algorithm (PSO)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(14), pages 4763-4777, November.
    2. Feng, Zhong-kai & Niu, Wen-jing & Wang, Wen-chuan & Zhou, Jian-zhong & Cheng, Chun-tian, 2019. "A mixed integer linear programming model for unit commitment of thermal plants with peak shaving operation aspect in regional power grid lack of flexible hydropower energy," Energy, Elsevier, vol. 175(C), pages 618-629.
    3. Bingke Yan & Bo Wang & Lin Zhu & Hesen Liu & Yilu Liu & Xingpei Ji & Dichen Liu, 2015. "A Novel, Stable, and Economic Power Sharing Scheme for an Autonomous Microgrid in the Energy Internet," Energies, MDPI, vol. 8(11), pages 1-24, November.
    4. Yuan, Xiaohui & Chen, Zhihuan & Yuan, Yanbin & Huang, Yuehua, 2015. "Design of fuzzy sliding mode controller for hydraulic turbine regulating system via input state feedback linearization method," Energy, Elsevier, vol. 93(P1), pages 173-187.
    5. Yulong Xu & Jian-an Fang & Wu Zhu & Xiaopeng Wang & Lingdong Zhao, 2015. "Differential evolution using a superior–inferior crossover scheme," Computational Optimization and Applications, Springer, vol. 61(1), pages 243-274, May.
    6. Mahalec, Vladimir & Chen, Yingwu & Liu, Xiaolu & He, Renjie & Sun, Kai, 2015. "Reconfiguration of satellite orbit for cooperative observation using variable-size multi-objective differential evolutionAuthor-Name: Chen, Yingguo," European Journal of Operational Research, Elsevier, vol. 242(1), pages 10-20.
    7. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    8. Schulze, Tim & McKinnon, Ken, 2016. "The value of stochastic programming in day-ahead and intra-day generation unit commitment," Energy, Elsevier, vol. 101(C), pages 592-605.
    9. Wen-chuan Wang & Wei-can Tian & Dong-mei Xu & Kwok-wing Chau & Qiang Ma & Chang-jun Liu, 2023. "Muskingum Models’ Development and their Parameter Estimation: A State-of-the-art Review," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(8), pages 3129-3150, June.
    10. Wang, Wenxiao & Li, Chaoshun & Liao, Xiang & Qin, Hui, 2017. "Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm," Applied Energy, Elsevier, vol. 187(C), pages 612-626.
    11. Siriporn Supratid & Thannob Aribarg & Seree Supharatid, 2017. "An Integration of Stationary Wavelet Transform and Nonlinear Autoregressive Neural Network with Exogenous Input for Baseline and Future Forecasting of Reservoir Inflow," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 4023-4043, September.
    12. Iman Ahmadianfar & Bijay Halder & Salim Heddam & Leonardo Goliatt & Mou Leong Tan & Zulfaqar Sa’adi & Zainab Al-Khafaji & Raad Z. Homod & Tarik A. Rashid & Zaher Mundher Yaseen, 2023. "An Enhanced Multioperator Runge–Kutta Algorithm for Optimizing Complex Water Engineering Problems," Sustainability, MDPI, vol. 15(3), pages 1-28, January.
    13. Dong, Jizhe & Han, Shunjie & Shao, Xiangxin & Tang, Like & Chen, Renhui & Wu, Longfei & Zheng, Cunlong & Li, Zonghao & Li, Haolin, 2021. "Day-ahead wind-thermal unit commitment considering historical virtual wind power data," Energy, Elsevier, vol. 235(C).
    14. Gejirifu De & Zhongfu Tan & Menglu Li & Liling Huang & Xueying Song, 2018. "Two-Stage Stochastic Optimization for the Strategic Bidding of a Generation Company Considering Wind Power Uncertainty," Energies, MDPI, vol. 11(12), pages 1-21, December.
    15. Shukla, Anup & Singh, S.N., 2016. "Advanced three-stage pseudo-inspired weight-improved crazy particle swarm optimization for unit commitment problem," Energy, Elsevier, vol. 96(C), pages 23-36.
    16. Wang, Bo & Zhou, Min & Xin, Bo & Zhao, Xin & Watada, Junzo, 2019. "Analysis of operation cost and wind curtailment using multi-objective unit commitment with battery energy storage," Energy, Elsevier, vol. 178(C), pages 101-114.
    17. Fazlalipour, Pary & Ehsan, Mehdi & Mohammadi-Ivatloo, Behnam, 2019. "Risk-aware stochastic bidding strategy of renewable micro-grids in day-ahead and real-time markets," Energy, Elsevier, vol. 171(C), pages 689-700.
    18. Chatterjee, Arunava & Roy, Krishna & Chatterjee, Debashis, 2014. "A Gravitational Search Algorithm (GSA) based Photo-Voltaic (PV) excitation control strategy for single phase operation of three phase wind-turbine coupled induction generator," Energy, Elsevier, vol. 74(C), pages 707-718.
    19. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    20. Wang, Bo & Wang, Shuming & Zhou, Xianzhong & Watada, Junzo, 2016. "Multi-objective unit commitment with wind penetration and emission concerns under stochastic and fuzzy uncertainties," Energy, Elsevier, vol. 111(C), pages 18-31.

    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:30:y:2016:i:8:d:10.1007_s11269-016-1321-y. 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.