Research Journal of Applied Sciences
Year:
2010
Volume:
5
Issue:
1
Page No.
20 - 26
References
Avinash, A., R.D. Singh, S.K. Mishra and P.K. Bhunya, 2005. ANN-based sediment yield models for Vamsadhara river basin (India). Water SA, 31: 95-100.
Direct Link | Bhattaacharya, B. and D.P. Solomatine, 2000. Application on artificial neural network in stage-discharge relationship. Proceedings of the 4th International Conference on Hydro Informatics, (ICHI'00), Lowa City, USA., pp: 1-7.
Clair, T.A. and J.M. Ehrman, 1996. Variations in discharge and dissolved organic carbon and nitrogen export from terrestrial basins with changes in climate: A neural network approach. Limnol. Oceanogr., 41: 921-927.
Direct Link | Dawson, C.W. and R. Wilby, 1998. An artificial neural network approach to rainfall-runoff modelling. J. Hydrol. Sci., 43: 47-66.
CrossRef | Direct Link | Dawson, C.W. and R.L. Wilby, 2001. Hydrological modeling using artificial neural network. Prog. Phys. Geogr., 1: 80-108.
Direct Link | Gasim, M.B., M.E. Toriman, A. Abas, M.S. Islam and T.C. Chek, 2008. The water quality of several feeder rivers between two seasons in Tasik Chini, Pahang. Sains Malaysiana, 37: 313-321.
Direct Link | Gasim, M.B., M.E.H. Toriman, Z.A. Rahman, M.S. Islam and T.C. Chek, 2009. Flow characteristics of the Tasik Chini's feeder rivers, Pahang, Malaysia. Bull. Geol. Soc. Malaysia, 75: 7-13.
Juahir, H., S.M. Zain, M.E. Toriman, M. Mokhtar and H.C. Man, 2004. Application of artificial neural network models for predicting water quality index. J. Kejuruteraan Awam, 16: 42-55.
Direct Link | Juahir, H., S.M. Zain, M.E. Toriman, M.N. Jaafar and W. Klaetanong, 2003. Performance of Autoregressive Integrated Moving Average and Neural Network Approaches for Forecasting Dissolved Oxygen at Langat River. In: Urban Ecosystem Studies in Malaysia: A Study of Change, Hashim, N.M. and R. Rainis (Eds). Universal Publishers, Florida, pp: 145-165.
Kamarudin, M.K.A., M.E. Toriman, S.A.S. Mastura, H. Mushrifah, I.N.R. Jamil and M.B. Gasim, 2009. Temporal variability on lowland river sediment properties and yield. Am. J. Environ. Sci., 5: 657-663.
CrossRef | Direct Link | Limin, F., 1996. Neural Networks in Computer Intelligence. McGraw Hill Inc., New York, pp: 460.
Mohamad, S. and M.E. Toriman, 2006. Implikasi struktur kunci air ke atas aktiviti pelancongan dan penduduk di sekitar sungai Chini dan Tasik Chini, Pahang. J. E-Bangi, 1: 1-13.
Direct Link | Najah, A., A. Elshafie, O.A. Karim and O. Jaffar, 2009. Prediction of Johor river water quality parameters using artificial neural networks. Eur. J. Sci. Res., 28: 422-435.
Direct Link | Sivakumar, B., A.W. Jayawardena and T.M.K.G. Fernando, 2002. River flow forecasting: Use of phase-space reconstruction and artificial neural networks approaches. J. Hydrol., 265: 225-245.
Direct Link | Solomatine, D.P. and L.A.A. Torres, 1996. Neural network approximation of a hydrodynamic model in optimising reservoir operation. Proceedings of the 2nd International Conference on Hydroinformatics, Sept. 9-13, Zurich, Switzerland, pp: 1-6.
Thirumalaiah, K. and M.C. Doe, 1998. River stage forecasting using artificial neural networks. J. Hydrol. Eng., 3: 26-32.
CrossRef | Toriman, M.E., 2004. Water balance analysis for agricultural development projects: The case of Western Johor, Peninsular Malaysia. Proceedings of the 3rd Annual Seminar Sustainability Science and Management, May 4-5, KUSTEM Publisher, pp: 105-109.
Toriman, M.E., H. Juahir, M. Mokhtar, M.B. Gazim, S.M.S. Abdullah and O. Jaafar, 2009. Predicting for discharge characteristics in Langat river, Malaysia using neural network application model. Res. J. Earth Sci., 1: 15-21.