Skip to main content
SpringerLink
Log in

Prediction of Discharge Capacity of Labyrinth Weir with Gene Expression Programming

  • Conference paper
  • First Online:
Intelligent Systems and Applications (IntelliSys 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1250))

Included in the following conference series:

Abstract

This paper proposes a model based on gene expression programming for predicting discharge coefficient of triangular labyrinth weirs. The parameters influencing discharge coefficient prediction were first examined and presented as crest height ratio to the head over the crest of the weir (p/y), crest length of water to channel width (L/W), crest length of water to the head over the crest of the weir (L/y), Froude number (F = V/√(gy)) and vertex angle (θ) dimensionless parameters. Different models were then presented using sensitivity analysis in order to examine each of the dimensionless parameters presented in this study. In addition, an equation was presented through the use of nonlinear regression (NLR) for the purpose of comparison with Gene Expression Programming (GEP). The results of the studies conducted by using different statistical indexes indicated that GEP is more capable than NLR. This is to the extent that GEP predicts discharge coefficient with an average relative error of approximately 2.5% in such manner that the predicted values have less than 5% relative error in the worst model.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Taylor, G.: The performance of labyrinth weir. Ph.D. thesis, University of Nottingham, Nottingham, England (1968)

    Google Scholar 

  2. Hay, N., Taylor, G.: A computer model for the determination of the performance of labyrinth weirs. In: 13th Congress of IAHR, Koyoto, Japan, pp. 361–378 (1969)

    Google Scholar 

  3. Tullis, J.P., Amanian, N., Waldron, D.: Design of labyrinth spillways. J. Hydraul. Eng. 121(3), 247–255 (1995)

    Google Scholar 

  4. Wormleaton, P.R., Soufiani, E.: Aeration performance of triangular planform labyrinth weirs. J. Environ. Eng. 124(8), 709–719 (1998)

    Google Scholar 

  5. Wormleaton, P.R., Tsang, C.C.: Aeration performance of rectangular planform labyrinth weirs. J. Environ. Eng. 126(5), 456–465 (2000)

    Google Scholar 

  6. Emiroglu, M.E., Baylar, A.: Influence of included angle and sill slope on air entrainment of triangular planform labyrinth weirs. J. Hydraul. Eng. 131(3), 184–189 (2005)

    Google Scholar 

  7. Tullis, B.P., Young, J.C., Chandler, M.A.: Head-discharge relationships for submerged labyrinth weirs. J. Hydraul. Eng. 133(3), 248–254 (2007)

    Google Scholar 

  8. Bagheri, S., Heidarpour, M.: Application of free vortex theory to estimating discharge coefficient for sharp-crested weirs. Biosys. Eng. 105(3), 423–427 (2010)

    Google Scholar 

  9. Kumar, S., Ahmad, Z., Mansoor, T.: A new approach to improve the discharging capacity of sharp-crested triangular plan form weirs. Flow Meas. Instrum. 22(3), 175–180 (2011)

    Google Scholar 

  10. Ebtehaj, I., Bonakdari, H.: Bed load sediment transport estimation in a clean pipe using multilayer perceptron with different training algorithms. KSCE J. Civil Eng. 20(2), 581–589 (2016). https://doi.org/10.1007/s12205-015-0630-7

    Article  Google Scholar 

  11. Bonakdari, H., Ebtehaj, I.: Verification of equation for non-deposition sediment transport in flood water canals. In: 7th International conference on fluvial hydraulics, River Flow, pp. 1527–1533 (2014)

    Google Scholar 

  12. Azimi, H., Bonakdari, H., Ebtehaj, I., Talesh, S.H.A., Michelson, D.G., Jamali, A.: Evolutionary Pareto optimization of an ANFIS network for modeling scour at pile groups in clear water condition. Fuzzy Sets Syst. 319, 50–69 (2017)

    MathSciNet  Google Scholar 

  13. Ebtehaj, I., Bonakdari, H.: Evaluation of sediment transport in sewer using artificial neural network. Eng. Appl. Comput. Fluid Mech. 7(3), 382–392 (2013)

    Google Scholar 

  14. Azimi, H., Bonakdari, H., Ebtehaj, I.: Sensitivity analysis of the factors affecting the discharge capacity of side weirs in trapezoidal channels using extreme learning machines. Flow Meas. Instrum. 54, 216–223 (2017)

    Google Scholar 

  15. Azimi, H., Bonakdari, H., Ebtehaj, I.: Design of radial basis function-based support vector regression in predicting the discharge coefficient of a side weir in a trapezoidal channel. Appl. Water Sci. 9(4), 1–12 (2019). https://doi.org/10.1007/s13201-019-0961-5

    Article  Google Scholar 

  16. Azimi, H., Shabanlou, S., Ebtehaj, I., Bonakdari, H., Kardar, S.: Combination of computational fluid dynamics, adaptive neuro-fuzzy inference system, and genetic algorithm for predicting discharge coefficient of rectangular side orifices. J. Irrig. Drain. Eng. 143(7), 04017015 (2017)

    Google Scholar 

  17. Ebtehaj, I., Bonakdari, H., Gharabaghi, B.: Development of more accurate discharge coefficient prediction equations for rectangular side weirs using adaptive neuro-fuzzy inference system and generalized group method of data handling. Measurement 116, 473–482 (2018)

    Google Scholar 

  18. Emiroglu, M.E., Kisi, O., Bilhan, O.: Predicting discharge capacity of triangular labyrinth side weir located on a straight channel by using an adaptive neuro-fuzzy technique. Adv. Eng. Softw. 41(2), 154–160 (2010)

    MATH  Google Scholar 

  19. Bilhan, O., Emiroglu, M.E., Kisi, O.: Application of two different neural network techniques to lateral outflow over rectangular side weirs located on a straight channel. Adv. Eng. Softw. 41(6), 831–837 (2010)

    MATH  Google Scholar 

  20. Emiroglu, M.E., Bilhan, O., Kisi, O.: Neural networks for estimation of discharge capacity of triangular labyrinth side-weir located on a straight channel. Expert Syst. Appl. 38(1), 867–874 (2011)

    MATH  Google Scholar 

  21. Azimi, H., Bonakdari, H., Ebtehaj, I.: Gene expression programming-based approach for predicting the roller length of a hydraulic jump on a rough bed. ISH J. Hydraul. Eng., 1–11 (2019). https://doi.org/10.1080/09715010.2019.1579058

  22. Bonakdari, H., Gharabaghi, B., Ebtehaj, I.: A highly efficient gene expression programming for velocity distribution at compound sewer channel. In: The 38th IAHR World Congress from September 1st to 6th, Panama City, Panama (2019). https://doi.org/10.3850/38WC092019-0221

  23. Ebtehaj, I., Bonakdari, H.: No-deposition sediment transport in sewers using gene expression programming. J. Soft Comput. Civil Eng. 1(1), 29–53 (2017)

    Google Scholar 

  24. Khozani, Z.S., Bonakdari, H., Ebtehaj, I.: An analysis of shear stress distribution in circular channels with sediment deposition based on gene expression programming. Int. J. Sedim. Res. 32(4), 575–584 (2017)

    Google Scholar 

  25. Khozani, Z.S., Bonakdari, H., Ebtehaj, I.: An expert system for predicting shear stress distribution in circular open channels using gene expression programming. Water Sci. Eng. 11(2), 167–176 (2018)

    Google Scholar 

  26. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. A Bradford Book, MIT Press, Cambridge (1992)

    MATH  Google Scholar 

  27. Azamathulla, H.M., Ahmad, Z., Ghani, A.A.: computation of discharge through side sluice gate using gene-expression programming. Irrig. Drain. 62(1), 115–119 (2013)

    Google Scholar 

  28. Ferreira, C.: Gene expression programming in problem solving, invited tutorial of the 6th online world conference on soft computing in industrial applications. In: Origins of Functionalist Theory, vol. 9, pp. 10–24 (2001)

    Google Scholar 

  29. Ferreira, C.: Gene expression programming: a new adaptive algorithm for solving problems. Complex Syst. 13, 87–129 (2001)

    MathSciNet  MATH  Google Scholar 

  30. Ferreira, C.: Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence, 2nd edn. Springer, Germany (2006)

    MATH  Google Scholar 

  31. Dursun, O.F., Kaya, N., Firat, M.: Estimating discharge coefficient of semi-elliptical side weir using ANFIS. J. Hydrol. 426, 55–62 (2012)

    Google Scholar 

  32. Legates, D.R., McCabe Jr., G.J.: Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour. Res. 35(1), 233–241 (1999)

    Google Scholar 

Download references

Acknowledgment

We acknowledge the financial support of this work by the Hungarian State and the European Union under the EFOP-3.6.1-16-2016-00010 project and the 2017-1.3.1-VKE-2017-00025 project. We also acknowledge the support of the German Research Foundation (DFG) and the Bauhaus-Universität Weimar within the Open-Access Publishing Programme.

Author information

Authors and Affiliations

  1. Department of Soils and Agri-Food Engineering, Laval University, Québec, G1V0A6, Canada

    Hossein Bonakdari & Isa Ebtehaj

  2. School of Engineering, University of Guelph, Guelph, ON, NIG 2W1, Canada

    Bahram Gharabaghi

  3. Department of Statistics, Razi University, Kermanshah, Iran

    Ali Sharifi

  4. Department of Mathematics and Informatics, J. Selye University, 94501, Komarno, Slovakia

    Amir Mosavi

  5. Kalman Kando Faculty of Electrical Engineering, Obuda University, Budapest, 1034, Hungary

    Amir Mosavi

  6. Institute of Structural Mechanics, Bauhaus-Universität Weimar, 99423, Weimar, Germany

    Amir Mosavi

Authors
  1. Hossein Bonakdari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Isa Ebtehaj
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bahram Gharabaghi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ali Sharifi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Amir Mosavi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hossein Bonakdari .

Editor information

Editors and Affiliations

  1. Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bonakdari, H., Ebtehaj, I., Gharabaghi, B., Sharifi, A., Mosavi, A. (2021). Prediction of Discharge Capacity of Labyrinth Weir with Gene Expression Programming. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1250. Springer, Cham. https://doi.org/10.1007/978-3-030-55180-3_17

Download citation

Publish with us

Policies and ethics

Search

Navigation