Sludge Bulking Prediction Using Principle Component Regression and Artificial Neural Network

  title={Sludge Bulking Prediction Using Principle Component Regression and Artificial Neural Network},
  author={Inchio Lou and Yuchao Zhao},
Sludge bulking is the most common solids settling problem in wastewater treatment plants, which is caused by the excessive growth of filamentous bacteria extending outside the flocs, resulting in decreasing the wastewater treatment efficiency and deteriorating the water quality in the effluent. Previous studies using molecular techniques have been widely used from the microbiological aspects, while the mechanisms have not yet been completely understood to form the deterministic cause-effect… CONTINUE READING


Publications referenced by this paper.
Showing 1-10 of 33 references

Prediction of activated sludge bulking based on a self-organizing RBF neural network,

  • H. G. Han, J. F. Qiao
  • Journal of Process Control,
  • 2012

Eutrophication in Macau main storage reservoir,

  • W. . Zhang, I. Lou, W. K. Ung, Y. Kong, K. M. Mok
  • Proceedings of the 12th International Conference…
  • 2011

The dynamics of cyanobacteria and microcystin production in a tropical reservoir of Singapore,

  • S. H. Te, K.Y.H. Gin
  • Harmful Algae, vol. 10,
  • 2011

Use of principal component scores in multiple linear regression models for prediction of Chlorophylla in reservoirs

  • N. Demýr H. Çamdevýren, A. Kanik, S. Keskýn
  • Environmental Modelling and Software
  • 2010

Artificial neural network approach for modelling and prediction of algal blooms

  • M. French, P. Harkonen, K. I. Yabunaka
  • Water Research
  • 2006

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