All Journal Publications

1- Zaji A.H., Bonakdari, H., Gharabaghi B., (2018), Remote Sensing Satellite Data Preparation for Simulating and Forecasting River Discharge, IEEE Transactions on Geoscience and Remote Sensing, Vol. PP, No. 99, pp. 1-10. doi: 10.1109/TGRS.2018.2799901.

 

2- Zaji A. H., Bonakdari, H., Gharabaghi B., (2018), Applying upstream satellite signals and a two-dimensional error minimization algorithm to advance early warning and management of flood water levels and river discharge, IEEE Transactions on Geoscience and Remote Sensing, Vol. PP, No. 99, pp. 1-9. doi: 10.1109/TGRS.2018.2862640.

 

3- Zaji A. H., Bonakdari, H., (2018), Velocity field simulation of open channel junction using artificial intelligence approaches, Iranian Journal of Science and Technology, Transactions of Civil Engineering. doi: 10.1007/s40996-018-0185-1.

 

4- Zaji A.H., Bonakdari, H., (2018), Robustness lake water level prediction using the search heuristic based artificial intelligence methods, ISH Journal of Hydraulic Engineering, doi: 10.1080/09715010.2018.1424568.

 

5- Zaji A.H., Bonakdari H., Shamshirband S., (2018), Standard equations for predicting the discharge coefficient of as modified high performance side weir, Scientia Iranica, Vol. 25, No. 3A, pp. 1057-1069, doi: 10.24200/sci.2017.4198.

 

6- Zaji A.H., Bonakdari H., Gharabaghi B. (2018). Reservoir water level forecasting using group method of data handling. Acta Geophysica, Vol. 66, No. 4, pp. 717-730. doi: 10.1007/s11600-018-0168-4.

 

7- Ebtehaj, I., Bonakdari, H., Zaji, A.H., Sharafi, H., (2018), Sensitivity analysis of parameters affecting scour depth around bridge piers based on the non-tuned, rapid extreme learning machine method, Neural Computing and Applications. DOI: 10.1007/s00521-018-3696-6.

 

8- Bonakdari H., Khozani Z.S., Zaji A.H., Asadpour N. (2018). Evaluating the apparent shear stress in prismatic compound channels using the Genetic Algorithm based on Multi-Layer Perceptron: A comparative study. Applied Mathematics and Computation, Vol. 338, pp. 400-411. doi: 10.1016/j.amc.2018.06.016.

 

9- Bonakdari H., Zaji A.H., Gharabaghi B., Ebtehaj I., Moazamnia M. (2018). More accurate prediction of the complex velocity field in sewers based on uncertainty analysis using extreme learning machine technique. ISH Journal of Hydraulic Engineering, doi: 10.1080/09715010.2018.1498753.

 

10- Sharifipour M., Bonakdari H., Zaji A.H., (2018), Comparison of genetic programming and radial basis function neural network for open channel junction velocity field prediction. Neural Computing and Applications, Vol. 30, No. 3, pp. 855-864. doi: 10.1007/s00521-016-2713-x.

 

11- Sheikh Khozani Z., Bonakdari H., Zaji A.H., (2018), Mean bed shear stress estimation in a rough rectangular channel using a hybrid genetic algorithm based on an articial neural network and genetic programming, Scientia Iranica, Vol. 25, No. 1, pp. 152-161.

 

12- Safarzadeh, A., Zaji A.H., Bonakdari, H., (2018), 3D flow simulation of straight groynes using hybrid DE-based artificial intelligence methods, Soft Computing, doi: 10.1007/s00500-018-3037-9.

 

13- Bonakdari, H., Zaji A.H., (2018), New type side weir discharge coefficient simulation using three novel hybrid adaptive neuro-fuzzy inference systems, Applied Water Science, Vol. 8, No. 15, pp. 1-15, doi: 10.1007/s13201-018-0669-y.

 

14- Sheikh Z., Bonakdari H., Zaji A.H., (2017), Estimating the shear stress distribution in circular channels based on the randomized neural network technique, Applied Soft Computing Journal, Vol. 58, pp. 441-448. DOI: 10.1016/j.asoc.2017.05.024.

 

15- Safarzadeh, A., Zaji A. H., Bonakdari, H., (2017), Comparative Assessment of the Hybrid Genetic Algorithm–Artificial Neural Network and Genetic Programming Methods for the Prediction of Longitudinal Velocity Field around a Single Straight Groyne. Applied Soft Computing, Vol. 60, pp. 213-228, DOI: 10.1016/j.asoc.2017.06.048.

 

16- Sheikh Z., Bonakdari H., Zaji A. H., (2017), Efficient shear stress distribution detection in circular channels using Extreme Learning Machines and the M5 model tree algorithm. Urban Water Journal, Vol. 14, No. 10, pp. 999-1006. DOI: 10.1080/1573062X.2017.1325495.

 

17- Zaji A. H., Bonakdari, H., (2017), Discharge and flow field simulation of open channel sewer junction using artificial intelligence methods, Scientia Iranica, doi: 10.24200/SCI.2018.20695.

 

18- Sheikh Z., Bonakdari H., Akhtari A. A., Zaji A. H., (2017), Estimating the shear force carried by walls in rough rectangular channels using a new approach based on the radial basis function method, International Journal of River Basin Management, Vol. 15, No. 3, pp. 309-305. DOI: 10.1080/15715124.2017.1307845.

 

19- Zaji A. H., Bonakdari H., (2017), Optimum support vector regression for discharge coefficient of modified side weirs prediction, INAE Letters, Vol. 2, pp. 25-33. DOI 10.1007/s41403-017-0018-8.

 

20- Gholami A., Bonakdari H., Zaji A. H., Ajeel Fenjan S., Akhatri A. A., (2017) New radial basis function network method based on decision trees to predict flow variables in a curved channel. Neural Computing and Applications, DOI: 10.1007/s00521-017-2875-1.

 

21- Sheikh Z., Bonakdari H., Zaji A. H., (2017), Using two soft computing methods to predict wall and bed shear stress in smooth rectangular channels, Applied Water Science, Vol. 7, No. 7, pp. 3973-3983. DOI: 10.1007/s13201-017-0548-y.

 

22- Moeeni H., Bonakdari H., Fatemi S. E., Zaji A. H., (2017), Assessment of Stochastic Models and a Hybrid Artificial Neural Network-Genetic Algorithm Method in Forecasting Monthly Reservoir Inflow, INAE Letters, Vol. 2, No. 1, pp. 13-23. doi: 10.1007/s41403-017-0017-9.

 

23- Ebtehaj I., Bonakdari, H., Zaji A. H., (2017), A new hybrid decision tree method based on two artificial neural networks for predicting sediment transport in clean pipes, Alexandria Engineering Journal, DOI: 10.1016/j.aej.2017.05.021.

 

24- Sheikh Z., Bonakdari H., Zaji A. H., (2017), Estimating shear stress in a rectangular channel with rough boundaries using an optimized SVM method, Neural Computing and Applications. DOI: 10.1007/s00521-016-2792-8.

 

25- Gholami A., Bonakdari H., Zaji A. H., Ajeel Fenjan S., Akhatri A. A., (2016), Developing finite volume method (FVM) in numerical simulation of flow pattern in 60° open channel bend, Journal of Applied Research in Water and Wastewater. Vol. 5, pp. 193-200.

 

26- Ebtehaj, I., Sattar A., Bonakdari, H., Zaji, A.H., (2016), Prediction of Scour Depth around Bridge Piers Using Self-Adaptive Extreme Learning Machine, Journal of Hydroinformatics. DOI: 10.2166/hydro.2016.025.

 

27- Sheikh Z., Bonakdari H., Zaji A. H., (2016), Comparison of Three Soft Computing Methods in Estimating Apparent Shear Stress in Compound Channels, International Journal of Engineering, Vo. 29, No. 9, pp. 1219-1226.

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28- Sharafi, H., Ebtehaj, I., Bonakdari, H., Zaji, A.H., (2016), Design of a Support Vector Machine with Different Kernel Functions to Predict Scour Depth around Bridge Piers, Natural Hazards. DOI: 10.1007/s11069-016-2540-5.

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29- Zaji A.H., Bonakdari H., Shamshirband S., (2016), Support vector regression for modified oblique side weirs discharge coefficient prediction, Flow Measurement and Instrumentation, Vol. 51, pp. 1-7, DOI: 10.1016/j.flowmeasinst.2016.08.006.

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30- Gholami A., Bonakdari H., Zaji A. H., Michelson D. G., Akhatri A. A., (2016), Improving the performance of multi-layer perceptron and radial basis function models with a decision tree model to predict flow variables in a sharp 90◦ bend, Applied Soft Computing, Vol. 48, pp. 563–583.

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31- Bonakdari H., Zaji A.H., (2016), Open channel junction velocity prediction by using a hybrid self-neuron adjustable artificial neural network, Flow Measurement and Instrumentation, Vol. 49, pp. 46-51. DOI: 10.1016/j.flowmeasinst.2016.04.003.

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32- Karimi S., Bonakdari H., Karami H., Gholami A., Zaji A. H., (2015), Effects of Width Ratios and Deviation Angles on the Mean Velocity in Inlet Channels Using Numerical Modeling and Artificial Neural Network Modeling, International Journal of Civil Engineering, Vol. 15, No. 2, pp. 149-161, DOI: 10.1007/s40999-016-0075-5.

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33- Ebtehaj I., Bonakdari H., Zaji A.H., (2016), An Expert System with Radial Basis Function Neural Network Based on Decision Trees for Predicting Sediment Transport in Sewers, Water Science & Technology, DOI: 10.2166/wst.2016.064.

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34- Ebtehaj I., Bonakdari H., Zaji A.H., (2016), A Nonlinear Simulation Method Based on a Combination of Multilayer Perceptron and Decision Tree for Predicting Non-deposition Sediment Transport, Water Science & Technology: Water Supply, DOI: 10.2166/ws.2016.034.

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35- Sheikh Z., Bonakdari H., Zaji A. H., (2016), Application of a genetic algorithm in predicting the percentage of shear force carried by walls in smooth rectangular channels, Measurement, Journal of the International Measurement Confederation, Vol. 87, pp. 87-98. Doi: 10.1016/j.measurement.2016.03.018.

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36- Ajeel Fenjan S., Bonakdari H., Gholami A., Zaji A. H., Akhatri A. A., (2016), Flow Variables Prediction Using Experimental, Computational Fluid Dynamic and Artificial Neural Network Models in a Sharp Bend, International Journal of Engineering, Vol. 29, No. 1, pp. 14-22. doi: 10.5829/idosi.ije.2016.29.01a.03.

 

37- Shamshirband S., Bonakdari H., Zaji A.H., Petković D., Motamedi S., (2016), Improved side weir discharge coefficient modeling by adaptive neuro-fuzzy methodology, KSCE Journal of Civil Engineering, DOI: 10.1007/s12205-016-1723-7.

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38- A., Bonakdari H., Zaji A. H., Ajeel Fenjan S., Akhatri A. A., (2016), Design of modified structure multi-layer perceptron networks based on decision trees for the prediction of flow parameters in a 90° open channel bends. Engineering Applications of Computational Fluid Mechanics, Vol. 10, No. 1, pp. 194-209. DOI: 10.1080/19942060.2015.1128358.

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39- Zaji A.H., Bonakdari H., Khodashenas S. R., Shamshirband S., (2016), Firefly optimization algorithm effect on support vector regression prediction improvement of a modified labyrinth side weir’s discharge coefficient, Applied Mathematics and Computation. Vol. 274, pp. 14-19. DOI: 10.1016/j.amc.2015.10.070.

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40- Sheikh Z., Bonakdari H., Zaji A. H., (2016), Application of a soft computing technique in predicting the percentage of shear force carried by walls in a rectangular channel with non-homogenous roughness, Water Science & Technology, Vol. 73, No. 1, pp. 124-129. DOI: 10.2166/wst.2015.470.

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41- Ebtehaj, I., Bonakdari, H., Zaji, A.H., Bong, C.H.J., Ghani, A.A. (2016), Design of a new hybrid artificial neural network method based on decision trees for predicting the incipient motion of sediment in rigid rectangular storm water channels, Journal of Hydrology and Hydromechanics, Vol. 64, No. 3, pp. 252-260.

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42- Karimi S., Bonakdari H., Ebtehaj I., Zaji A. H., (2015), Prediction of Mean Velocity in Open Channel Intake Using Numerical Model and Gene Expression Programming, Mitteilungen Saechsischer Entomologen, Vol. 119, pp. 599-616.

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43- Zaji A.H., Bonakdari H., Karimi S. (2015), Radial Basis Neural Network and Particle Swarm Optimization-based equations for predicting the discharge capacity of triangular labyrinth weirs, Flow Measurement and Instrumentation, Vol. 45, pp 341-347.

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44- Sharifipour M., Bonakdari H., Zaji A. H., (2015), Impact of the confluence angle on flow field and flowmeter accuracy in open channel junctions, International Journal of Engineering, Vol. 28, No. 8, pp 1145-1153.

 

45- Ebtehaj I. , Bonakdari H. , Zaji A.H., Azimi H., Sharifi A., (2015), Gene Expression Programming to Predict the Discharge Coefficient in Rectangular Side Weirs, Applied Soft Computing, Vol. 35, pp 618-628.

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46- Zaji A.H., Bonakdari H., Shamshirband S., Qasem S.N., (2015), Potential of particle swarm optimization based radial basis function network to predict the discharge coefficient of a modified triangular side weir. Flow Measurement and Instrumentation, Vol. 45, pp. 404-407. DOI: 10.1016/j.flowmeasinst.2015.06.007.

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47- Khoshbin F., Bonakdari H., Ashraf Talesh S. H., Ebtehaj I., Zaji A. H., Azimi H., (2015), ANFIS multi-objective optimization using Genetic Algorithm Singular Value Decomposition method for modeling discharge coefficient in rectangular sharp-crested side weirs, Engineering Optimization. DOI:10.1080/0305215X.2015.1071807.

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48- Bonakdari H., Zaji A.H., Shamshirband S., Hashim R., Petković D., (2015), Sensitivity analysis of the discharge coefficient of a modified triangular side weir by adaptive neuro-fuzzy methodology, Measurement, DOI: 10.1016/j.measurement.2015.05.021.

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49- Gholami A., Bonakdari H., Zaji A. H., Akhtari A.A., (2015), Simulation of open channel bend characteristics using computational fluid dynamics and artificial neural network, Engineering Application of Computational Fluid Mechanics Journal, DOI:10.1080/19942060.2015.1033808.

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50- Ebtehaj I., Bonakdari H., Zaji A. H., Azimi H, Khoshbin F., (2015), GMDH-Type neural network approach for modeling of discharge coefficient rectangular sharp-crested side weirs, Engineering Science and Technology: an International Journal. DOI: 10.1016/j.jestch.2015.04.012.

 

51- Sharifipour M., Bonakdari H., Zaji A. H., Shamshirband S., (2015), Numerical investigation of flow field and flowmeter accuracy in open-channel junctions. Engineering Applications of Computational Fluid Mechanics, Vol. 9, No. 1, pp. 280-290. DOI: 10.1080/19942060.2015.1008963.

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52- Zaji A.H., Bonakdari H., (2015), Efficient methods for prediction of velocity fields in open channel junctions based on the artificial neural network, Engineering Application of Computational Fluid Mechanics Journal, Vol. 9, No. 1, pp.220-232. DOI: 10.1080/19942060.2015.1004821.

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53- Zaji A.H., Bonakdari H., (2015), Application of artificial neural network and genetic programming models for estimating the longitudinal velocity field in open channel junctions. Flow Measurement and Instrumentation, Vol. 41, pp. 81-89. DOI: 10.1016/j.flowmeasinst.2014.10.011.

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54- Gholami A., Bonakdari H., Zaji A. H., Akhtari A. A., Khodashenas S. R., (2015), Predicting the velocity field in a 90 open channel bend using a gene expression programming model, Flow Measurement and Instrumentation, Vol. 46, Part A, pp. 189-192, DOI: 10.1016/j.flowmeasinst.2015.10.006.

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55- Zaji A.H., Bonakdari H., (2014), Performance evaluation of two different neural network and particle swarm optimization methods for prediction of discharge capacity of modified triangular side weirs. Flow Measurement and Instrumentation. Vol. 40, pp. 149-156. DOI: 10.1016/j.flowmeasinst.2014.10.002.

 

56- Karimi S., Bonakdari H., Zaji A. H., (2015), Numerical Examination of the Relative Effect of the Channel Width in the Intakes on the Velocity Distribution Curves in the Flow Deviation Location, Journal of Civil and Environmental Engineering, Vol. 45, No. 1: pp 93-102.