Abstract
In order to allow the key stakeholders to have more float time to take appropriate precautionary and preventive measures, an accurate prediction of water quality pollution is very significant. Since a variety of existing water quality models involve exogenous input and different assumptions, artificial neural networks have the potential to be a cost-effective solution. This paper presents the application of a split-step particle swarm optimization (PSO) model for training perceptrons to forecast real-time algal bloom dynamics in Tolo Harbour of Hong Kong. The advantages of global search capability of PSO algorithm in the first step and local fast convergence of Levenberg-Marquardt algorithm in the second step are combined together. The results demonstrate that, when compared with the benchmark backward propagation algorithm and the usual PSO algorithm, it attains a higher accuracy in a much shorter time.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chau, K.-w., Cheng, C.T.: Real-time prediction of water stage with artificial neural network approach. In: McKay, B., Slaney, J.K. (eds.) Canadian AI 2002. LNCS (LNAI), vol. 2557, pp. 715–715. Springer, Heidelberg (2002)
Rumelhart, D.E., Widrow, B., Lehr, M.A.: The Basic Ideas in Neural Networks. Communications of the ACM 37, 87–92 (1994)
Hagan, M.T., Menhaj, M.B.: Training Feedforward Networks with the Marquardt Algorithm. IEEE Transactions on Neural Networks 5, 989–993 (1994)
Kennedy, J., Eberhart, R.: Particle Swarm Optimization. In: Proceedings of the 1995 IEEE International Conference on Neural Networks, Perth, pp. 1942–1948 (1995)
Chau, K.W.: River Stage Forecasting with Particle Swarm Optimization. In: Orchard, B., Yang, C., Ali, M. (eds.) IEA/AIE 2004. LNCS (LNAI), vol. 3029, pp. 1166–1173. Springer, Heidelberg (2004)
Chau, K.W.: Rainfall-Runoff Correlation with Particle Swarm Optimization Algorithm. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 970–975. Springer, Heidelberg (2004)
Kennedy, J.: The Particle Swarm: Social Adaptation of Knowledge. In: Proceedings of the 1997 International Conference on Evolutionary Computation, Indianapolis, pp. 303–308 (1997)
Clerc, M., Kennedy, J.: Explosion, Stability, and Convergence in a Multidimensional Complex Space. IEEE Transactions on Evolutionary Computation 6, 58–73 (2002)
Chau, K.W., Jin, H.S.: Eutrophication Model for a Coastal Bay in Hong Kong. Journal of Environmental Engineering ASCE 124, 628–638 (1998)
Chau, K.W., Jin, H.S., Sin, Y.S.: A Finite Difference Model of Two-Dimensional Tidal Flow in Tolo Harbor, Hong Kong. Applied Mathematical Modelling 20, 321–328 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chau, K. (2005). A Split-Step PSO Algorithm in Prediction of Water Quality Pollution. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3498. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427469_164
Download citation
DOI: https://doi.org/10.1007/11427469_164
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25914-5
Online ISBN: 978-3-540-32069-2
eBook Packages: Computer ScienceComputer Science (R0)