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Application of Artificial Neuro-Fuzzy Logic Inference System for Predicting the Microbiological Pollution in Fresh Water

Author(s): S. Bouharati | K. Benmahammed | D. Harzallah | Y.M. El-Assaf

Journal: Journal of Applied Sciences
ISSN 1812-5654

Volume: 8;
Issue: 2;
Start page: 309;
Date: 2008;
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Keywords: Testing water | E. coli detection | fuzzy expert system | hybrid intelligent system | artificial neuro-fuzzy logic inference

The classical methods for detecting the micro biological pollution in water are based on the detection of the coliform bacteria which indicators of contamination. But to check each water supply for these contaminants would be a time-consuming job and a qualify operators. In this study, we propose a novel intelligent system which provides a detection of microbiological pollution in fresh water. The proposed system is a hierarchical integration of an Artificial Neuro-Fuzzy Inference System (ANFIS). This method is based on the variations of the physical and chemical parameters occurred during bacteria growth. The instantaneous result obtained by the measurements of the variations of the physical and chemical parameters occurred during bacteria growth-temperature, pH, electrical potential and electrical conductivity of many varieties of water (surface water, well water, drinking water and used water) on the number Escherichia coli in water. The instantaneous result obtained by measurements of the inputs parameters of water from sensors.
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