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Optimal control of prawn aquaculture water quality index using artificial neural networks

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2 Author(s)
Gustilo, R.C. ; DLSU, Manila, Philippines ; Dadios, E.

The water quality index (wqi) of the artificial habitat for prawn aquaculture is monitored and controlled by an artificial neural network. The states of the five critical parameters needed for an optimal aquaculture environment are monitored and tuned to go to their corresponding optimal values, allowing the water quality index to go and stay to its optimal state. This optimal setting will improve the artificial habitat for aquaculture systems. Results show that the five critical parameters for artificial habitat can be monitored properly and set to their optimal states. The system is designed using parameters for tiger prawns but is capable to be adjusted for any species raised in aquaculture farming. The system can be used for real time aquaculture environment control.

Published in:

Cybernetics and Intelligent Systems (CIS), 2011 IEEE 5th International Conference on

Date of Conference:

17-19 Sept. 2011