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Evaluation of pool water quality of trout farms by fuzzy logic: monitoring of pool water quality for trout farms

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Abstract

Pool water must have a certain quality parameters for the vital processes of trout. For this purpose, monitoring of a pool water quality of trout farms is realized using fuzzy logic with graphical user interface (GUI). Pool water qualities of four trout farms with different sources were investigated in terms of chemical oxygen demand, ammonium nitrogen, pH and electrical conductivity parameters during 270 days of study period between August 2011 and April 2012. The resulting data set created a 21 × 32-sized matrix for all parameters. Comparison between input and output waters of pools is made with SPSS (PASW 18) software for parameter changes in the pools. It would be too difficult for the observer researcher to interpret this set, a computer program was developed with fuzzy logic system, the decision-making tool, to graphically present the Turkish Water Pollution Control by laws state in pool water quality. Fuzzy logic was used in the evaluation of these data and notification of the critical states which exceeded the limiting values. The classification of the product of the quality characteristics is performed by human experts due to the absence of measuring devices. The program is developed to graphically present the conditions regarding pool water quality with GUI. Fuzzy logic results are presented on the monitors. The results enable even those people with inadequate knowledge about the subject to comment on pool water quality of farms. This software increases awareness of the water quality.

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Acknowledgments

The data acquired with farms were obtained from scientific research project with project number of 2011.09.04.418 that was managed by Dr. Arda Yalcuk. We would like to thank project group.

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Yalcuk, A., Postalcioglu, S. Evaluation of pool water quality of trout farms by fuzzy logic: monitoring of pool water quality for trout farms. Int. J. Environ. Sci. Technol. 12, 1503–1514 (2015). https://doi.org/10.1007/s13762-014-0536-9

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  • DOI: https://doi.org/10.1007/s13762-014-0536-9

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