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Neural Based pH System in Effluent Treatment Process

Author

Listed:
  • B. Meenakhsipriya
  • K. Saravanan
  • S. Sathiyavathi

Abstract

This investigation considers the application of Artificial Neural Network (ANN) techniques to estimate the pH value for effluent treatment process. ANN has the ability to identify the non-linear dynamical systems from the input-output data. An important requirement of the application is robustness of the system against erroneous sensor measurements. The simulation model of the pH system for common effluent treatment plant (CETP) is developed using MATLAB 7.5, GUI tool box. A novel off-line and on-line training scheme for the neural network is developed by error back propagation training algorithm to model the pH system for CETP, accurately. For this purpose, a simple feed forward, back propagation neural network, with only one hidden layer, and sigmoidal activation functions is used. The training of such network is based on Input-Output data which is collected from Perundurai common effluent treatment plant (PCETP). Experimentation and simulation results on this neuro identifier of pH system for common effluent treatment plant are shown.

Suggested Citation

  • B. Meenakhsipriya & K. Saravanan & S. Sathiyavathi, 2009. "Neural Based pH System in Effluent Treatment Process," Modern Applied Science, Canadian Center of Science and Education, vol. 3(4), pages 166-166, April.
    • Handle: RePEc:ibn:masjnl:v:3:y:2009:i:4:p:166
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    References listed on IDEAS

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    1. B. Meenakshipriya & K. Saravanan & R. Shanmugam & S. Sathiyavathi, 2008. "Study of pH System in Common Effluent Treatment Plant," Modern Applied Science, Canadian Center of Science and Education, vol. 2(4), pages 113-113, July.
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      JEL classification:

      • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
      • Z0 - Other Special Topics - - General

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