Full Length Research Paper
References
| Abrahart RJ, Kneale PE, See LM (2005). Neural networks for hydrological modelling. Taylor & Francis, LONDON, UK. | ||||
|
Abrahart RJ, See LM, Heppenstall AJ, White SM (2008). Neural Network Estimation of Suspended Sediment: Potential Pitfalls and Future Directions. In: Abrahart RJ, See LM, Solomatine DP (eds) Practical Hydroinformatics, vol. 68. Water Science and Technology Library. Springer Berlin Heidelberg, pp. 139-161. CrossRef |
||||
|
Achite M, Ouillon S (2007). Suspended sediment transport in a semiarid watershed, Wadi Abd, Algeria (1973-1995). J. Hydrol. 343:187-202. CrossRef |
||||
| Adib A, Tagavifar A (2010). Evaluation and Comparison Different Methods of Preparation of Sediment Rating Curve in Telezang Station of the Dez River. Austr. J. Basic Appl. Sci. 4(5):717-723 | ||||
|
ASCE TC (2000) Artificial Neural Networks in Hydrology II. Hydrologic Applications. J. Hydrol. Eng. 5:124-137. CrossRef |
||||
|
Asselman NEM (2000). Fitting and interpretation of sediment rating curves. J. Hydrol. 234:228-248. CrossRef |
||||
|
Boukhrissa ZA, Khanchoul K, Le Bissonnais Y, Tourki M (2013). Prediction of sediment load by sediment rating curve and neural network (ANN) in El Kebir catchment, Algeria. J. Earth Syst. Sci. 122:1303-1312. CrossRef |
||||
|
Chandramouli V, Deka P (2005) Neural Network Based Decision Support Model for Optimal Reservoir Operation. Water Resour. Manag. 19:447-464 CrossRef |
||||
| Chaves P, Chang FJ (2008). Intelligent reservoir operation system based on evolving artificial neural networks. Elsevier, Kidlington, ROYAUME-UNI. 31(6):926-936. | ||||
|
Chen ZY (2014). A Hybrid Algorithm by Combining Swarm Intelligence Methods and Neural Network for Gold Price Prediction. In: Wang LL, June J, Lee CH, Okuhara K, Yang HC (eds) Multidisciplinary Social Networks Research, 473. Communications in Computer and Information Science. Springer Berlin Heidelberg, pp. 404-416. CrossRef |
||||
| Chutachindakate C (2009). Integrated sediment approach and impacts of climate change on reservoir sedimentation. Kyoto University. | ||||
| Cigizoglu HK (2008). Artificial Neural Networks In Water Resources. In. pp.115-148. | ||||
|
Cigizoglu HK, Alp M (2006). Generalized regression neural network in modelling river sediment yield Adv. Eng. Softw. 37:63-68. CrossRef |
||||
|
Cigizoglu HK, Kisi O (2006). Methods to improve the neural network performance in suspended sediment estimation. J. Hydrol. 317:221-238 CrossRef |
||||
|
Cohn TA, Delong LL, Gilroy EJ, Hirsch RM, Wells DK (1989). Estimating constituent loads. Water Resour. Res. 25:937-942. CrossRef |
||||
|
Daliakopoulos IN, Coulibaly P, Tsanis IK (2005). Groundwater level forecasting using artificial neural networks. J. Hydrol. 309(1-4):229-240. CrossRef |
||||
| Dhar V (2010). Comparative performance of some popular artifcial neural network algorithms on benchmark and function approximation problems PRAMANA. J. Phys. 74(2):307-324. | ||||
|
Dolling OR, Varas EA (2002). Artificial neural networks for stream flow prediction. J. Hydraul. Res. 40(5):547-554. CrossRef |
||||
|
Eslamian S, Lavaei N (2009). Modelling nitrate pollution of groundwater using artificial neural network and genetic algorithm in an arid zone. Int. J. Water. 5(2):194-203. CrossRef |
||||
|
Firat M, Güngör M (2010). Monthly total sediment forecasting using adaptive neuro fuzzy inference system. Stoch. Environ. Res. Risk Assess. 24:259-270. CrossRef |
||||
|
Hasebe M, Nagayama Y (2002). Reservoir operation using the neural network and fuzzy systems for dam control and operation support Adv. Eng. Softw. 33:245-260 doi:http://dx.doi.org/10.1016/S0965-9978(02)00015-7 http://dx.doi.org/10.1016/S0965-9978(02)00015-7 |
||||
| Horowitz AJ (2002).The use of rating (Transport) curves to predict suspended sediment concentration: Am matter of temporal resolution. Paper presented at the Turbidity and Other Sediment Surrogates Workshop, Reno, NV. | ||||
|
Julien PY (2010). Erosion and Sedimentation (2nd Edition). Cambridge University Press. CrossRef |
||||
|
Kalteh AM (2013). Monthly river flow forecasting using artificial neural network and support vector regression models coupled with wavelet transform. Comput. Geosci. 54:1-8 CrossRef |
||||
|
Kennedy J, Eberhart R (1995). Particle swarm optimization. Neural Networks, 1995.Proceedings IEEE Int. Conf. 4:942-1948. 68. CrossRef |
||||
|
Khanchoul K, El Abidine Boukhrissa Z, Acidi A, Altschul R (2010). Estimation of suspended sediment transport in the Kebir drainage basin, Algeria Quaternary International In Press, CrossRef |
||||
|
Khanchoul K, Jansson MB (2008). Sediment Rating Curves Developed On Stage And Seasonal Means In Discharge Classes For The Mellah Wadi, Algeria Geografiska Annaler: Series A, Phys. Geogr. 90:227-236. doi:10.1111/j.1468-0459.2008.341.x. CrossRef |
||||
|
Kim D-IJaY-O (2005). Rainfall-runoff models using artificial neural networks for ensemble stream flow prediction Hydrol. Processes 19:3819-3835 CrossRef |
||||
|
Kisi O (2005) Suspended sediment estimation using neuro-fuzzy and neural network approaches. Hydrol. Sci. J. 50(4):683-696 CrossRef |
||||
|
Kisi O (2012). Modeling discharge-suspended sediment relationship using least square support vector machine J. Hydrol. 456-457:110-120. CrossRef |
||||
| Kisi Ö (2007). Development of Streamflow-Suspended Sediment Rating Curve Using a Range Dependent Neural Network. Int. J. Sci. Technol. 2(1):49-61. | ||||
|
Kisi O, Dailr AH, Cimen M, Shiri J (2012a). Suspended sediment modeling using genetic programming and soft computing techniques. J. Hydrol. 450-451:48-58. CrossRef |
||||
|
Kisi O, Ozkan C, Akay B (2012b). Modeling discharge–sediment relationship using neural networks with artificial bee colony algorithm. J. Hydrol. 428–429:94-103. CrossRef |
||||
|
Liu QJ, Shi ZH, Fang NF, Zhu HD, Ai L (2013). Modeling the daily suspended sediment concentration in a hyperconcentrated river on the Loess Plateau, China, using the Wavelet–ANN approach. Geomorphology 186:181-19. CrossRef |
||||
| Nagesh K (2004). ANN Applications in Hydrology - Merits and Demerits, Integrated Water Resources Planning and Management. Jain Brothers, New Delhi. | ||||
|
Rajaee T, Nourani V, Zounemat-Kermani M, Kisi O (2011). River Suspended Sediment Load Prediction: Application of ANN and Wavelet Conjunction Model. J. Hydrol. Eng. 16(8):613-627. doi:doi:10.1061/(ASCE)HE.1943-5584.0000347. CrossRef |
||||
|
Ramezani F, Nikoo M, Nikoo M (2014). Artificial neural network weights optimization based on social-based algorithm to realize sediment over the river. Soft Comput. pp.1-13 doi:10.1007/s00500-014-1258-0. CrossRef |
||||
| Shamim MA, Ghumman AR, Ghani U (2004). Forecasting Groundwater Contamination Using Artificial Neural Networks. Paper presented at the International Conference on Water Resources and Arid Environment, King Saud University, Riyadh, Saudi Arabia. | ||||
| Sivanandam SN, Deepa SN (2006). Introduction to Neural Networks Using Matlab 6.0. Tata McGraw-Hill. | ||||
| Sreekanth PD, Geethanjali N, Sreedevi PD, Ahmed S, Kumar NR, Jayanthi PDK (2009). Forecasting groundwater level using artificial neural networks. Curr. Sci. 96(7):933-939. | ||||
|
Tebbi FZ, Dridi H, Morris GL (2012). Optimization of cumulative trapped sediment curve for an arid zone reservoir: Foum El Kherza (Biskra, Algeria). Hydrol. Sci. J. 57:1368-1377. CrossRef |
||||
| Terfous A, Megnounif A, Bouanani A (2001). Etude du transport solide en suspension dans l'Oued Mouilah (Nord Ouest Algérien). Rev. Sci. Eau. 14:173-185. | ||||
|
Touaibia B, Aidaoui A, Gomer D, Achite M (2001). Temporal quantification and variability of sediment discharge in a semiarid area in northern Algeria. Hydrol. Sci. J. 46:41-53. CrossRef |
||||
| Walling DE (1977). Limitations of the rating curve technique for estimating suspended sediment loads, with particular reference to British rivers. Paper presented at the Erosion and Solid Matter Transport in Inland Waters, Paris. | ||||
| Wang Y-M, Traore S, Kerh T (2008). Using artificial neural networks for modeling suspended sediment concentration. Paper presented at the Proceedings of the 10th WSEAS International Conference on Mathematical Methods and Computational Techniques in Electrical Engineering, Sofia, Bulgaria. | ||||
Copyright © 2024 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0
