Abstract
A study on application of data-driven models namely the rule-based model based on mamdani Fuzzy Logic and Artificial Neural Network model in predicting dissolved oxygen in an effluent-impacted urban river is presented and compared. Combined rule bases were formed from the generated fuzzy rules for input – output mapping. Predictability of both the models was good with better performance for the ANN model. With ANN model, it is possible to obtain an output by simulating the model with the parameters of the best-fit model. A relationship connecting the selected parameters not considered previously to assess dissolved oxygen could also be established.
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