Browsing by Author "Patki, V.K."

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    Fuzzy system modeling for forecasting water quality index in municipal distribution system
    (2015) Patki, V.K.; Shrihari, S.; Manu, B.; Deka, P.C.
    An attempt has been made to develop a fuzzy expert system capable of establishing a criterion for predicting water quality index (WQI) in the various zones of municipal distribution system using pH, alkalinity, hardness, dissolved oxygen (DO), total solids (TS) and most probable number (MPN). The proposed expert system includes a fuzzy model consisting of IF-THEN rules to determine WQI based on water quality characteristics. The fuzzy models are developed using triangular and trapezoidal membership functions, with centroid, bisector and mean of maxima (MOM) methods for defuzzification. Further, the performance of fuzzy models is compared with adaptive neuro fuzzy inference (ANFIS) models. ANFIS models are developed by using triangular, trapezoidal, bell and Gaussian membership function. The study reveals that fuzzy models outperform ANFIS models for all water quality classes. Out of twenty nine zones in the study area, for twenty two zones fuzzy model with triangular membership function performs better than trapezoidal membership function and, for sixteen zones, the centroid method, for seven zones bisector and for remaining six zones MOM method of defuzzification performs better. 2013, 2013 Taylor & Francis.
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    Fuzzy system modeling for forecasting water quality index in municipal distribution system
    (Taylor and Francis Ltd., 2015) Patki, V.K.; Shrihari, S.; Manu, B.; Deka, P.C.
    An attempt has been made to develop a fuzzy expert system capable of establishing a criterion for predicting water quality index (WQI) in the various zones of municipal distribution system using pH, alkalinity, hardness, dissolved oxygen (DO), total solids (TS) and most probable number (MPN). The proposed expert system includes a fuzzy model consisting of IF-THEN rules to determine WQI based on water quality characteristics. The fuzzy models are developed using triangular and trapezoidal membership functions, with centroid, bisector and mean of maxima (MOM) methods for defuzzification. Further, the performance of fuzzy models is compared with adaptive neuro fuzzy inference (ANFIS) models. ANFIS models are developed by using triangular, trapezoidal, bell and Gaussian membership function. The study reveals that fuzzy models outperform ANFIS models for all water quality classes. Out of twenty nine zones in the study area, for twenty two zones fuzzy model with triangular membership function performs better than trapezoidal membership function and, for sixteen zones, the centroid method, for seven zones bisector and for remaining six zones MOM method of defuzzification performs better. © 2013, © 2013 Taylor & Francis.