Assessment of evolutionary algorithms in predicting non-deposition sediment transport

Urban Water Journal

Volumn 13, Issue 5, 2016, Pages 499-510

  Ebtehaj, Isa ^a   Bonakdari, Hossein ^a  

^a RAZI UNIVERSITY   (Iran)

Author keywords

densimetric Froude number; imperialist competitive algorithms (ICA); non deposition; particle swarm optimization (PSO); sediment; sewer

Indexed keywords

ALGORITHM; FROUDE NUMBER; OPTIMIZATION; SEDIMENT TRANSPORT; SEWER NETWORK;

EID: 84922354942     PISSN: 1573062X     EISSN: 17449006     Source Type: Journal    
DOI: 10.1080/1573062X.2014.994003     Document Type: Article

References (47)

1. A.Ab. Ghani,, 1993. Sediment transport in sewers, Thesis (PhD). University of Newcastle Upon Tyne, UK.
2. M.Abdollahi,, A.Isazadeh,, and D.Abdollahi,, 2013. Imperialist competitive algorithm for solving systems of nonlinear equations. Computers and Mathematics with applications, 65 (2), 1894–1908.
3. J.C.Ackers,, D.Butler,, and R.W.P.May,, 1996. Design of sewers to control sediment problems. Rep. No. CIRIA 141. London: Construction Industry Research and Information Association.
4. M.H.Afshar, and R.Rajabpour,, 2009. Application of local and global particle swarm optimization algorithms to optimal design and operation of irrigation pumping systems. Irrigation and drainage, 58 (3), 321–331.
5. J.Almedeij,, 2012. Rectangular storm sewer design under equal sediment mobility. American Journal of Environmental Science, 8 (4), 376–384.
6. ASCE, 1970. Design and construction of sanitary and storm sewers. Manual and Reports on Engineering Practices, No. 37. New York: American Society of Civil Engineers.
7. E.Atashpaz-Gargari, and C.Lucas,, 2007. Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. IEEE Congress on Evolutionary Computation, 7, 4661–4666.
8. ATV-DVWK-Regelwerk, 2001. Hydraulische Dimensionierung und Leistungsnachweis von Abwasserkanalen und-leitungen, Arbeitsblatt, AVT-DVWK-A 110. Hennef, Germany: German Association for Water, Wastewater and Waste.
9. A.Azadnia, and B.Zahraie,, 2010. Application of multi-objective particle swarm optimization in operation management of reservoirs with sedimentation problems. In: World Environmental and Water Resources Congress 2010. Reston, VA, USA: American Society of Civil Engineers, 2260–2268.
10. S.Baghalian,, H.Bonakdari,, F.Nazari,, and M.Fazli,, 2012. Closed-form solution for flow field in curved channels in comparison with experimental and numerical analyses and artificial neural network. Engineering Application of Computational Fluid Mechanics, 6 (4), 514–526.
11. H.Bonakdari,, S.Baghalian,, F.Nazari,, and M.Fazli,, 2011. Numerical analysis and prediction of the velocity field in curved open channel using artificial neural network and genetic algorithm. Engineering Application of Computational Fluid Mechanics, 5 (3), 384–396.
12. H.Brombach,, S.Michelbach,, and C.Wohrle,, 1992. Sedimentations- und Remobilisierungsvorgänge im Abwasserkanal. Bad Mergentheim, Germany: BMFT Joint Project Precipitation.
13. BS8005-1, 1987. Sewerage Guide to New Sewerage Construction. London: British Standard Institution.
14. D.Butler,, R.May,, and J.Ackers,, 2003. Self-cleansing sewer design based on sediment transport principles. Journal of Hydraulic Engineering, 129 (4), 276–282.
15. I.Ebtehaj, and H.Bonakdari,, 2013. Evaluation of sediment transport in sewer using artificial neural network. Engineering Applications of Computational Fluid Mechanics, 7 (3), 382–392.
16. I.Ebtehaj,, H.Bonakdari,, and A.Sharifi,, 2014. Design criteria for sediment transport in sewers based on self-cleansing concept. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 15 (11), 914–924.
17. European Standard EN 752-4, 1997. Drain and sewer system outside building: Part 4.Hydraulic design and environmental considerations. Brussels: CEN (European Committee for Standardization).
18. J.Kennedy,, 1998. The behavior of particles. In: V.W.Porto, N.Saravanan, D.Waagen and A.E.Eiben, eds. Evolutionary Programming VII. Springer, 581–590.
19. J.Kennedy, and R.Eberhart,, 1995. Particle swarm optimization. In: Proceedings of the International Conference on Neural Networks. Perth, Western Australia: The University of Western Australia, 1942–1948.
20. O.Kisi,, 2008. River flow forecasting and estimation using different artificial neural network techniques. Hydrology Research, 39 (1), 27–40.
21. T.Khanna,, 1990. Foundations of neural networks. Boston, MA, USA: Addison-Wesley Company.
22. V.Kachitvichyanukul,, 2012. Comparison of Three Evolutionary Algorithms: GA, PSO, and DE. Industrial Engineering & Management Systems, 11 (3), 215–223.
23. J.Y.Lin,, C.T.Cheng,, and K.W.Chau,, 2006. Using support vector machines for long-term discharge prediction. Hydrological Sciences Journal, 51 (4), 599–612.
24. O.G.Lindholm,, 1984. Pollutant loads from combined sewer systems. In: Proceedings of the 3rd International Conference on Urban storm drainage. Gothenburg, Sweden: Almqvist & Wiksell International, 1602–1616.
25. D.K.Lysne,, 1969. Hydraulic design of self-cleaning sewage tunnels. Journal of the Sanitary Engineering Division, ASCE, 95 (SA1), 17–36.
26. E.Macke,, 1982. About sediment at low concentrations in partly filled pipes. Leichtweiss–Institut fur Wasserbau der Technischen Universitat Braunschweig, Heft 76.
27. R.W.P.May,, 1993. Sediment transport in pipes and sewers with deposited beds. Report SR 320Wallingford, UK: Hydraulic Research.
28. R.W.P.May,, P.M.Brown,, G.R.Hare,, and K.D.Jones,, 1989. Self-cleansing condition for sewers carrying sediment. Report SR 221Wallingford, UK: Hydraulic Research.
29. R.W.P.May,, J.C.Ackers,, D.Butler,, and S.John,, 1996. Development of design methodology for self-cleansing sewers. Water Science and Technology, 33 (9), 195–205.
30. R.Mayerle,, C.Nalluri,, and P.Novak,, 1991. Sediment transport in rigid bed conveyance. Journal of Hydraulic Research, 29 (4), 475–495.
31. I.Montalvo,, J.Izquierdo,, and M.M.Tung,, 2008. Particle swarm optimization applied to the design of water supply systems. Computers and Mathematics with applications, 56 (3), 769–776.
32. M.Muzzammil,, 2008. Application of neural networks to scour depth prediction at the bridge abutments. Engineering Application of Computational Fluid Mechanics, 2 (1), 30–40.
33. C.Nalluri, and A.Ab.Ghani,, 1993. Bed load transport without deposition in channel of circular section. In: Proceedings of the Sixth International Conference on Urban Storm Drainage. Niagara Falls, Canada: Seapoint Publishing, 625–630.
34. C.Nalluri, and A.Ab. Ghani,, 1996. Design option for self-cleansing storm sewers. Water Science and Technology, 33 (9), 215–220.
35. C.Nalluri,, A.Ab. Ghani,, and A.K.El-Zaemey,, 1994. Sediment transport over deposited beds in sewers. Water Science and Technology, 29 (1–2), 125–133.
36. P.Novak, and C.Nalluri,, 1975. Sediment transport in smooth fixed bed channels. Journal of Hydraulic Division, ASCE, 101 (9), 1139–1154.
37. J.J.Ota, and C.Nalluri,, 2003. Urban storm sewer design in consideration of sediment. Journal of Hydraulic Engineering, 129 (4), 291–297.
38. J.J.Ota,, C.Nalluri,, and G.Perrusquia,, 1999. Graded sediment transport - the influence of particle size on sediment transport over deposited loose beds in sewers. In: 8th International Conference on Urban Storm Drainage. vol. 2. Sydney, Australia: IWA Publishing, 626–634.
39. J.J.Ota, and G.S.Perrusquía,, 2013. Particle velocity and sediment transport at the limit of deposition in sewers. Water Science and Technology, 67 (5), 959–967.
40. Y.Shi, and R.C.Eberhart,, 1998. Parameter selection in particle swarm optimization. In: V.W.Porto, N.Saravanan, D.Waagen and A.E.Eiben, eds. Evolutionary programming VII, Lecture Notes in Computer Science, 1447. Berlin, Heidelberg: Springer, 611–616.
41. Y.Shi, and R.C.Eberhart,, 1999. Empirical study of particle swarm optimization. In: Proceedings of IEEE, International Congress Evolutionary Computation. Piscataway, NJ, USA: IEEE Xplore Digital Library, 1945–1950.
42. G.Tayfur, and V.Guldal,, 2006. Artificial neural networks for estimating daily total suspended sediment in natural streams. Nordic Hydrology, 37 (1), 69–79.
43. S.A.Vaghefi,, S.Mousavi,, K.C.Abbaspour,, and H.Yang,, 2012. An imperialist competitive algorithm artificial neural network method to predict runoff. In: Proceeding of EGU General Assembly 2012, Vienna, Austria, 14, EGU2012-484-2.
44. N.Vongvisessomjai,, T.Tingsanchali,, and M.S.Babel,, 2010. Non-deposition design criteria for sewers with part-full flow. Urban Water Journal, 7 (1), 61–77.
45. W.C.Wang,, K.W.Chau,, C.T.Cheng,, and L.Qiu,, 2009. A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series. Journal of Hydrology, 374 (3–4), 294–306.
46. C.L.Wu,, K.W.Chau,, and C.Fan,, 2010. Prediction of rainfall time series using modular artificial neural networks coupled with data-preprocessing techniques. Journal of Hydrology, 389 (1–2), 146–167.
47. K.M.Yao,, 1974. Sewer line design based on critical shear stress. Journal of the Environmental Engineering Division, ASCE, 100 (EE2), 507–520.