Optimization / Classification Algorithm

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), Robustness lake water level prediction using the search heuristic based artificial intelligence methods, ISH Journal of Hydraulic Engineering, doi: 10.1080/09715010.2018.1424568.

 

 

4- 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.

 

 

5- 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.

 

 

6- 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.

 

 

7- 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.

 

 

8- 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.

 

 

9- 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.

 

 

10- 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.

 

 

11- 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.

 

 

12- 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.

 

 

13- 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.

 

 

14- 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.

 

 

15- 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.

 

 

16- 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.

 

 

17- 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.

 

 

18- 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.

 

 

19- 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.

 

 

20- 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.

​

21- 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.

​

22- 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.

​

23- 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.

​

24- 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.

​

25- 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.