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Research Papers

Improving water quality index prediction in Perak River basin Malaysia through a combination of multiple neural networks

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Pages 79-87 | Received 06 Apr 2016, Accepted 22 Oct 2016, Published online: 23 Nov 2016

References

  • Ahmad, Z. and Zhang, J., 2009. Selective combination of multiple neural networks for improving model prediction in nonlinear systems modelling through forward selection and backward elimination. Neurocomputing, 72, 1198–1204. doi: 10.1016/j.neucom.2008.02.005
  • Antonopoulos, V.Z., Papamichail, D.M., and Mitsiou, K.A., 2001. Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece. Hydrology and Earth System Sciences, 5, (4), 679–692. doi: 10.5194/hess-5-679-2001
  • ASMA, 2012. River water quality monitoring. Available from: http://www.doe.gov.my/portalv1/en/general-info/pemantauan-kualiti-air-sungai/280 [Accessed 01.07.12].
  • Bishop, C., 1995. Neural networks for pattern recognition. Oxford: Clarendon Press.
  • Boyacioglu, H., 2006. Surface water quality assessment using factor analysis. Water South Africa, 32 (3), 389–393.
  • Cho, K.H., et al., 2011. Prediction of contamination potential of ground water arsenic in Cambodia, Laos, and Thailand using artificial neural network. Water Research, 45, 5535–5544. doi: 10.1016/j.watres.2011.08.010
  • Dhalla, P., et al., 2008. Quick and reliable estimation of BOD load of beverage industrial wastewater by developing BOD biosensor. Sensors and Actuators B: Chemical, 133, 478–483. doi: 10.1016/j.snb.2008.03.010
  • Faruk, O.D., 2010. A hybrid neural network and ARIMA model for water quality time series prediction. Engineering Applications of Artificial Intelligence, 23 (4), 586–594. doi: 10.1016/j.engappai.2009.09.015
  • Han, H.G., Chen, Q.L., and Qiao, J.F., 2011. An efficient self-organizing RBF neural network for water quality prediction. Neural Networks, 24 (7), 717–725. doi: 10.1016/j.neunet.2011.04.006
  • Khan, R.A., et al., 2001. Using principal component scores and artificial neural networks in predicting water quality index. Chemometrics in Practical Applications, 271–288.
  • Khuan, L.Y., Hamzah, N., and Jailani, R., 2002. Prediction of water quality index (WQI) based on artificial neural network (ANN). In 2002 Student conference on research and development proceedings. Shah Alam, Malaysia, 157–161.
  • Li, M. and Hassan, R., 2006. Urban air pollution forecasting using artificial intelligence-based tools. Air Pollution, 195–220.
  • Loucks, D.P. and van Beek, E., 2005. Water resources systems planning and management: an introduction to methods, models and applications. Paris: UNESCO Press.
  • Mamun, A.A., Hafizah, S.N., and Alam, M.Z., 2009. Improvement of existing water quality index in Selangor, Malaysia. In 2nd International conference on water & flood management (ICWFM), 15–17 March 2009, Dhaka, Bangladesh.
  • McLoone, S. and Irwin, G., 2001. Improving neural networks training solution using regularization. Neurocomputing, 37, 71–90. doi: 10.1016/S0925-2312(00)00314-3
  • Rabiatul, M.N. and Zainal, A., 2012. Optimum numbers of single network for combination in multiple neural networks modeling approach for modeling nonlinear system optimum. IIUM Eng Journal, 12 (6), 45–58.
  • Thoe, W., et al., 2014. Predicting water quality at Santa Monica beach: evaluation of five different models for public notification of unsafe swimming conditions. Water Research, 67, 105–117. doi: 10.1016/j.watres.2014.09.001
  • Xu, L. and Liu, S., 2013. Study of short-term water quality prediction model based on wavelet neural network. Mathematical and Comput Modelling, 58 (3–4), 807–813. doi: 10.1016/j.mcm.2012.12.023
  • Zhang J, et al., 1998. Prediction of polymer quality in batch polymerization reactors using robust neural networks. Chemical Engineering Journal, 69, 135–143. doi: 10.1016/S1385-8947(98)00069-2
  • Zhang, J., 1999. Developing robust non-linear models through bootstrap aggregated neural networks. Neurocomputing, 25, 93–113. doi: 10.1016/S0925-2312(99)00054-5

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