Document Type : Research Paper
Authors
1 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran.
2 Department of Civil Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran. Soil Conservation and Watershed Management Research Institute, (SCWMRI), Tehran, Iran. Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.
10.22126/arww.2023.7934.1255
Abstract
In this paper, the ANFIS network was optimized using three algorithms comprising the Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), and Genetic algorithm (GA) for the first time. To ameliorate the ability of the numerical models,
the Monte Carlo simulations were utilized. Moreover, in order to assess the simulation outcomes, the k-fold cross validation technique was implemented. Initially, using all inputs, five different parameters were used for producing the
ANFIS, ANFIS-GA, ANFIS-PSO, and ANFIS-FFA methods. After that, a computational fluid dynamics (CFD) model simulated the discharge coefficient (DC) and the outcome of all simulations were compared. The analysis of the results demonstrated that the ANFIS-FFA model approximates the DC with higher precision. For instance, the amount of the coefficient of determination and the scatter index were surmised as 0.961 and 0.039. Also, the side weir height ratio to
the upstream depth (P/y1) was detected as the most influential parameter. About 85% of the DC simulated by the ANFIS-FFA model had an inaccuracy of less than 5%. The performed uncertainty analysis proved that the best model possesses an underestimated efficiency. For this model, the influence of the inputs were analyzed in a ±10% range. Finally, a computational code was presented for the simulation of DC by hydraulic and environmental engineers.
Keywords
Abdollahi A., Kabiri-Samani A., Asghari K., Atoof H., Bagheri S.,
Numerical modeling of flow field around the labyrinth side-weirs in the
presence of guide vanes, ISH Journal of Hydraulic Engineering 23
(2017) 71-79.
Abdulshahed A.M., Longstaff A.P., Fletcher S., The application of
ANFIS prediction models for thermal error compensation on CNC
machine tools, Applied Soft Computing 27 (2015) 158-168.
Ameri M., Dehghani A.A., Ahmadi A., Elementary discharge coefficient
of a triangular–rectangular sharp-crested side weir in subcritical flow,
International Journal of River Basin Management 14 (2016) 95-102.
Aydin M. C., Investigation of a sill effect on rectangular side-weir flow
by using CFD, Journal of Irrigation and Drainage Engineering 142
(2015) 04015043.
Aydin M.C., New approach for estimation of rectangular side weirs
discharge in subcritical flow, Journal of Irrigation and Drainage
Engineering 142 (2016) 04016012.
Aydin M.C., Emiroglu M.E., Determination of capacity of labyrinth side
weir by CFD, Flow Measurement and Instrumentation 29 (2013) 1-8.
Aydin M.C., Emiroglu M.E., Numerical analysis of subcritical flow over
two-cycle trapezoidal labyrinth side weir, Flow Measurement and
Instrumentation 48 (2016) 20-28.
Aydin M.C., Öztürk M., Yücel A., Experimental and numerical
investigation of self-priming siphon side weir on a straight open
channel, Flow Measurement and Instrumentation 45 (2015) 140-150.
Azamathulla H.M., Haghiabi A.H., Parsaie A., Prediction of side weir
discharge coefficient by support vector machine technique, Water
Science and Technology: Water Supply 16 (2016) 1002-1016.
Azimi H., Shabanlou S., The flow pattern in triangular channels along
the side weir for subcritical flow regime, Flow Measurement and
Instrumentation 46 (2015) 170-178.
Azimi H., Shabanlou S., U-shaped channels along the side weir for
subcritical and supercritical flow regimes, ISH Journal of Hydraulic
Engineering (2018) 1-11.
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 Measurement and
Instrumentation 54 (2017) 216-223.
Azimi H., Bonakdari H., Ebtehaj I., Michelson D.G.A., combined
adaptive neuro-fuzzy inference system–firefly algorithm model for
predicting the roller length of a hydraulic jump on a rough channel
bed, Neural Computing and Applications 29 (2018a) 249-258.
Azimi H., Bonakdari H., Ebtehaj I., Gharabaghi B., Khoshbin F.,
Evolutionary design of generalized group method of data handlingtype
neural network for estimating the hydraulic jump roller length,
ActaMechanica 229 (2018b) 1197-1214.
Azimi H., Shabanlou S., Salimi M.S., Free surface and velocity field in a
circular channel along the side weir in supercritical flow conditions,
Flow Measurement and Instrumentation 38 (2014) 108-115.
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, Journal of Irrigation and
Drainage Engineering 143 (2017) 04017015.
Bagheri S., Kabiri-Samani A. R., Heidarpour M., Discharge coefficient
of rectangular sharp-crested side weirs, Part I: traditional weir Eq.,
Flow Measurement and Instrumentation 35 (2014) 109-115.
Chatterjee S., Mahapatra S.S., Lamberti L., Pruncu C.I., Prediction of
welding responses using AI approach: adaptive neuro-fuzzy
inference system and genetic programming, Journal of the Brazilian
Society of Mechanical Sciences and Engineering 44 (2022) 1-15.
Crispino G., Cozzolino L., Della Morte R., Gisonni C., Supercritical lowcrested
bilateral weirs: hydraulics and design procedure, Journal of
Applied Water Engineering and Research 3 (2015) 35-42.
Dursun O.F., Kaya N., Firat M., Estimating discharge coefficient of
semi-elliptical side weir using ANFIS, Journal of hydrology 426
(2012) 55-62.
Numerical modeling of flow field around the labyrinth side-weirs in the
presence of guide vanes, ISH Journal of Hydraulic Engineering 23
(2017) 71-79.
Abdulshahed A.M., Longstaff A.P., Fletcher S., The application of
ANFIS prediction models for thermal error compensation on CNC
machine tools, Applied Soft Computing 27 (2015) 158-168.
Ameri M., Dehghani A.A., Ahmadi A., Elementary discharge coefficient
of a triangular–rectangular sharp-crested side weir in subcritical flow,
International Journal of River Basin Management 14 (2016) 95-102.
Aydin M. C., Investigation of a sill effect on rectangular side-weir flow
by using CFD, Journal of Irrigation and Drainage Engineering 142
(2015) 04015043.
Aydin M.C., New approach for estimation of rectangular side weirs
discharge in subcritical flow, Journal of Irrigation and Drainage
Engineering 142 (2016) 04016012.
Aydin M.C., Emiroglu M.E., Determination of capacity of labyrinth side
weir by CFD, Flow Measurement and Instrumentation 29 (2013) 1-8.
Aydin M.C., Emiroglu M.E., Numerical analysis of subcritical flow over
two-cycle trapezoidal labyrinth side weir, Flow Measurement and
Instrumentation 48 (2016) 20-28.
Aydin M.C., Öztürk M., Yücel A., Experimental and numerical
investigation of self-priming siphon side weir on a straight open
channel, Flow Measurement and Instrumentation 45 (2015) 140-150.
Azamathulla H.M., Haghiabi A.H., Parsaie A., Prediction of side weir
discharge coefficient by support vector machine technique, Water
Science and Technology: Water Supply 16 (2016) 1002-1016.
Azimi H., Shabanlou S., The flow pattern in triangular channels along
the side weir for subcritical flow regime, Flow Measurement and
Instrumentation 46 (2015) 170-178.
Azimi H., Shabanlou S., U-shaped channels along the side weir for
subcritical and supercritical flow regimes, ISH Journal of Hydraulic
Engineering (2018) 1-11.
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 Measurement and
Instrumentation 54 (2017) 216-223.
Azimi H., Bonakdari H., Ebtehaj I., Michelson D.G.A., combined
adaptive neuro-fuzzy inference system–firefly algorithm model for
predicting the roller length of a hydraulic jump on a rough channel
bed, Neural Computing and Applications 29 (2018a) 249-258.
Azimi H., Bonakdari H., Ebtehaj I., Gharabaghi B., Khoshbin F.,
Evolutionary design of generalized group method of data handlingtype
neural network for estimating the hydraulic jump roller length,
ActaMechanica 229 (2018b) 1197-1214.
Azimi H., Shabanlou S., Salimi M.S., Free surface and velocity field in a
circular channel along the side weir in supercritical flow conditions,
Flow Measurement and Instrumentation 38 (2014) 108-115.
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, Journal of Irrigation and
Drainage Engineering 143 (2017) 04017015.
Bagheri S., Kabiri-Samani A. R., Heidarpour M., Discharge coefficient
of rectangular sharp-crested side weirs, Part I: traditional weir Eq.,
Flow Measurement and Instrumentation 35 (2014) 109-115.
Chatterjee S., Mahapatra S.S., Lamberti L., Pruncu C.I., Prediction of
welding responses using AI approach: adaptive neuro-fuzzy
inference system and genetic programming, Journal of the Brazilian
Society of Mechanical Sciences and Engineering 44 (2022) 1-15.
Crispino G., Cozzolino L., Della Morte R., Gisonni C., Supercritical lowcrested
bilateral weirs: hydraulics and design procedure, Journal of
Applied Water Engineering and Research 3 (2015) 35-42.
Dursun O.F., Kaya N., Firat M., Estimating discharge coefficient of
semi-elliptical side weir using ANFIS, Journal of hydrology 426
(2012) 55-62.
Ebtehaj I., and Bonakdari H., Assessment of evolutionary algorithms in predicting non-deposition sediment transport, Urban Water Journal 13 (2016) 499-510.
Ebtehaj I., Bonakdari H., Khoshbin F., Azimi H., Pareto genetic design of group method of data handling type neural network for prediction discharge coefficient in rectangular side orifices, Flow Measurement and Instrumentation 41 (2015) 67-74.
Ebtehaj I., Bonakdari H., Shamshirband S., Ismail Z., Hashim R., New approach to estimate velocity at limit of deposition in storm sewers using vector machine coupled with firefly algorithm, Journal of Pipeline Systems Engineering and Practice 8 (2017) 04016018.
Ebtehaj I., Bonakdari H., A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes, Water Science and Technology 73 (2016) 2244-2250.
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 Systems with Applications 38 (2011) 867-874.
Emiroglu M.E., Gogus M., Tunc M., Islamoglu K., Effects of Antivortex Structures Installed on Trapezoidal Labyrinth Side Weirs on Discharge Capacity and Scouring, Journal of Irrigation and Drainage Engineering 143 (2017) 04017006.
Ferreira C.V., Biesek F.L., Scalice R.K., Product innovation management model based on manufacturing readiness level (MRL), design for manufacturing and assembly (DFMA) and technology readiness level (TRL), Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (2021) 1-18.
Freitas F.A., Jafelice R.M., Silva J.W.D., Rabelo D.D.S., Nomelini Q.S.S., Moura J.D.R.V.D., Ramos J.E., A new data normalization approach applied to the electromechanical impedance method using adaptive neuro-fuzzy inference system, Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (2021) 1-13.
Gholami A., Bonakdari H., Ebtehaj I., Mohammadian M., Gharabaghi B., Khodashenas S.R., Uncertainty analysis of intelligent model of hybrid genetic algorithm and particle swarm optimization with ANFIS to predict threshold bank profile shape based on digital laser approach sensing, Measurement 121 (2018) 294-303
Goldberg D.E., Holland J.H., Genetic algorithms and machine learning. Machine learning 3 (1988) 95-99.
Granata F., Gargano R., Santopietro S., A flow field characterization in a circular channel along a side weir. Flow Measurement and Instrumentation 52 (2016) 92-100.
Jang J.S., ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics 23 (1993) 665-685.
Karimi M., Attari J., Saneie M., JaliliGhazizadeh M.R., Side Weir Flow Characteristics: Comparison of Piano Key, Labyrinth, and Linear Types, Journal of Hydraulic Engineering 144 (2018) 04018075.
Kennedy R., Particle swarm optimization, In Proceedings of IEEE International Conference on Neural Networks IV Vol. 1000 (1995) p. 33.
Khameneh H.Z., Khodashenas S.R., Esmaili K., The effect of increasing the number of cycles on the performance of labyrinth side weir, Flow Measurement and Instrumentation 39 (2014) 35-45.
Khoshbin F., Bonakdari H., Ashraf Talesh S.H., Ebtehaj I., Zaji A.H., Azimi H., Adaptive neuro-fuzzy inference system multi-objective optimization using the genetic algorithm/singular value decomposition method for modelling the discharge coefficient in rectangular sharp-crested side weirs, Engineering Optimization 48 (2016) 933-948.
Kisi O., Emiroglu M.E., Bilhan O., Guven A., Prediction of lateral outflow over triangular labyrinth side weirs under subcritical conditions using soft computing approaches, Expert systems with Applications 39 (2012) 3454-3460.
Mahmodinia S., Javan M., Eghbalzadeh A., The effects of side-weir height on the free surface turbulent flow, KSCE Journal of Civil Engineering 18 (2014) 2244-2251.
Novak G., Steinman F., Müller M., Bajcar T., Study of velocity field at model sideweir using visualization method, Journal of Hydraulic Research 50 (2012) 129-133.
Onen F., Agaccioglu H., Live bed scour at a side‐weir intersection located on an alluvial channel. Irrigation and Drainage 62 (2013) 488-500.
Paris E., Solari L., Bechi G., Applicability of the De Marchi hypothesis for side weir flow in the case of movable beds, Journal of Hydraulic Engineering 138 (2012) 653-656.
Parsaie A., Haghiabi A., The effect of predicting discharge coefficient by neural network on increasing the numerical modeling accuracy of flow over side weir, Water resources management 29 (2015) 973-985.
Parsaie A., Yonesi H., Najafian S., Prediction of flow discharge in compound open channels using adaptive neuro fuzzy inference system method, Flow Measurement and Instrumentation 54 (2017) 288-297.
Qasem N.M., Ebtehaj I., Bonakdari H., Potential of radial basis function network with particle swarm optimization for prediction of sediment transport at the limit of deposition in a clean pipe, Sustainable Water Resources Management 3 (2017) 391-401.
Roushangar K., Khoshkanar R., Shiri J., Predicting trapezoidal and rectangular side weirs discharge coefficient using machine learning methods, ISH Journal of Hydraulic Engineering 22 (2016) 254-261.
Sai T., Pathak V.K., Srivastava A.K., Modeling and optimization of fused deposition modeling (FDM) process through printing PLA implants using adaptive neuro-fuzzy inference system (ANFIS) model and whale optimization algorithm, Journal of the Brazilian Society of Mechanical Sciences and Engineering 42 (2020) 1-19.
Shafiei S., Najarchi M., Shabanlou S., A novel approach using CFD and neuro-fuzzy-firefly algorithm in predicting labyrinth weir discharge coefficient, Journal of the Brazilian Society of Mechanical Sciences and Engineering 42 (2020) 1-19.
Shaghaghi S., Bonakdari H., Gholami A., Ebtehaj I., Zeinolabedini M., Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design, Applied Mathematics and Computation 313 (2017) 271-286.
Shihabudheen K.V., Pillai G.N., Recent advances in neuro-fuzzy system: A survey, Knowledge-Based Systems 152 (2018) 136-162.
Yang X.S., Firefly algorithm, Nature-inspired metaheuristic algorithms 20 (2008) 79-90.
Yaseen Z.M., Ebtehaj I., Bonakdari H., Deo R.C., Mehr A.D., Mohtar W.H.M.W., Diop L., El-shafie A., Singh V.P., Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model, Journal of Hydrology 554C (2017) 263-276.
Yaseen Z.M., Ghareb M.I., Ebtehaj I., Bonakdari H., Siddique R., Heddam S., Yusif A., Deo R., Rainfall pattern forecasting using novel hybrid intelligent model based ANFIS-FFA, Water Resources Management 32 (2018) 105-122.
Zahiri A., Azamathulla H.M., Bagheri S., Discharge coefficient for compound sharp crested side weirs in subcritical flow conditions, Journal of hydrology 480 (2013) 162-166.
Ebtehaj I., Bonakdari H., Khoshbin F., Azimi H., Pareto genetic design of group method of data handling type neural network for prediction discharge coefficient in rectangular side orifices, Flow Measurement and Instrumentation 41 (2015) 67-74.
Ebtehaj I., Bonakdari H., Shamshirband S., Ismail Z., Hashim R., New approach to estimate velocity at limit of deposition in storm sewers using vector machine coupled with firefly algorithm, Journal of Pipeline Systems Engineering and Practice 8 (2017) 04016018.
Ebtehaj I., Bonakdari H., A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes, Water Science and Technology 73 (2016) 2244-2250.
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 Systems with Applications 38 (2011) 867-874.
Emiroglu M.E., Gogus M., Tunc M., Islamoglu K., Effects of Antivortex Structures Installed on Trapezoidal Labyrinth Side Weirs on Discharge Capacity and Scouring, Journal of Irrigation and Drainage Engineering 143 (2017) 04017006.
Ferreira C.V., Biesek F.L., Scalice R.K., Product innovation management model based on manufacturing readiness level (MRL), design for manufacturing and assembly (DFMA) and technology readiness level (TRL), Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (2021) 1-18.
Freitas F.A., Jafelice R.M., Silva J.W.D., Rabelo D.D.S., Nomelini Q.S.S., Moura J.D.R.V.D., Ramos J.E., A new data normalization approach applied to the electromechanical impedance method using adaptive neuro-fuzzy inference system, Journal of the Brazilian Society of Mechanical Sciences and Engineering 43 (2021) 1-13.
Gholami A., Bonakdari H., Ebtehaj I., Mohammadian M., Gharabaghi B., Khodashenas S.R., Uncertainty analysis of intelligent model of hybrid genetic algorithm and particle swarm optimization with ANFIS to predict threshold bank profile shape based on digital laser approach sensing, Measurement 121 (2018) 294-303
Goldberg D.E., Holland J.H., Genetic algorithms and machine learning. Machine learning 3 (1988) 95-99.
Granata F., Gargano R., Santopietro S., A flow field characterization in a circular channel along a side weir. Flow Measurement and Instrumentation 52 (2016) 92-100.
Jang J.S., ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man, and Cybernetics 23 (1993) 665-685.
Karimi M., Attari J., Saneie M., JaliliGhazizadeh M.R., Side Weir Flow Characteristics: Comparison of Piano Key, Labyrinth, and Linear Types, Journal of Hydraulic Engineering 144 (2018) 04018075.
Kennedy R., Particle swarm optimization, In Proceedings of IEEE International Conference on Neural Networks IV Vol. 1000 (1995) p. 33.
Khameneh H.Z., Khodashenas S.R., Esmaili K., The effect of increasing the number of cycles on the performance of labyrinth side weir, Flow Measurement and Instrumentation 39 (2014) 35-45.
Khoshbin F., Bonakdari H., Ashraf Talesh S.H., Ebtehaj I., Zaji A.H., Azimi H., Adaptive neuro-fuzzy inference system multi-objective optimization using the genetic algorithm/singular value decomposition method for modelling the discharge coefficient in rectangular sharp-crested side weirs, Engineering Optimization 48 (2016) 933-948.
Kisi O., Emiroglu M.E., Bilhan O., Guven A., Prediction of lateral outflow over triangular labyrinth side weirs under subcritical conditions using soft computing approaches, Expert systems with Applications 39 (2012) 3454-3460.
Mahmodinia S., Javan M., Eghbalzadeh A., The effects of side-weir height on the free surface turbulent flow, KSCE Journal of Civil Engineering 18 (2014) 2244-2251.
Novak G., Steinman F., Müller M., Bajcar T., Study of velocity field at model sideweir using visualization method, Journal of Hydraulic Research 50 (2012) 129-133.
Onen F., Agaccioglu H., Live bed scour at a side‐weir intersection located on an alluvial channel. Irrigation and Drainage 62 (2013) 488-500.
Paris E., Solari L., Bechi G., Applicability of the De Marchi hypothesis for side weir flow in the case of movable beds, Journal of Hydraulic Engineering 138 (2012) 653-656.
Parsaie A., Haghiabi A., The effect of predicting discharge coefficient by neural network on increasing the numerical modeling accuracy of flow over side weir, Water resources management 29 (2015) 973-985.
Parsaie A., Yonesi H., Najafian S., Prediction of flow discharge in compound open channels using adaptive neuro fuzzy inference system method, Flow Measurement and Instrumentation 54 (2017) 288-297.
Qasem N.M., Ebtehaj I., Bonakdari H., Potential of radial basis function network with particle swarm optimization for prediction of sediment transport at the limit of deposition in a clean pipe, Sustainable Water Resources Management 3 (2017) 391-401.
Roushangar K., Khoshkanar R., Shiri J., Predicting trapezoidal and rectangular side weirs discharge coefficient using machine learning methods, ISH Journal of Hydraulic Engineering 22 (2016) 254-261.
Sai T., Pathak V.K., Srivastava A.K., Modeling and optimization of fused deposition modeling (FDM) process through printing PLA implants using adaptive neuro-fuzzy inference system (ANFIS) model and whale optimization algorithm, Journal of the Brazilian Society of Mechanical Sciences and Engineering 42 (2020) 1-19.
Shafiei S., Najarchi M., Shabanlou S., A novel approach using CFD and neuro-fuzzy-firefly algorithm in predicting labyrinth weir discharge coefficient, Journal of the Brazilian Society of Mechanical Sciences and Engineering 42 (2020) 1-19.
Shaghaghi S., Bonakdari H., Gholami A., Ebtehaj I., Zeinolabedini M., Comparative analysis of GMDH neural network based on genetic algorithm and particle swarm optimization in stable channel design, Applied Mathematics and Computation 313 (2017) 271-286.
Shihabudheen K.V., Pillai G.N., Recent advances in neuro-fuzzy system: A survey, Knowledge-Based Systems 152 (2018) 136-162.
Yang X.S., Firefly algorithm, Nature-inspired metaheuristic algorithms 20 (2008) 79-90.
Yaseen Z.M., Ebtehaj I., Bonakdari H., Deo R.C., Mehr A.D., Mohtar W.H.M.W., Diop L., El-shafie A., Singh V.P., Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model, Journal of Hydrology 554C (2017) 263-276.
Yaseen Z.M., Ghareb M.I., Ebtehaj I., Bonakdari H., Siddique R., Heddam S., Yusif A., Deo R., Rainfall pattern forecasting using novel hybrid intelligent model based ANFIS-FFA, Water Resources Management 32 (2018) 105-122.
Zahiri A., Azamathulla H.M., Bagheri S., Discharge coefficient for compound sharp crested side weirs in subcritical flow conditions, Journal of hydrology 480 (2013) 162-166.
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