Modelling and Prediction of Water Quality by Using Artificial Intelligence

نویسندگان

چکیده

Artificial intelligence methods can remarkably reduce costs for water supply and sanitation systems help ensure compliance with the quality of drinking wastewater treatment. Therefore, modelling predicting to control pollution has been widely researched. The novelty proposed system is presented develop an efficient operation monitoring a sustainable friendly green environment. In this work, adaptive neuro-fuzzy inference (ANFIS) algorithm was developed predict index (WQI). Feed-forward neural network (FFNN) K-nearest neighbors were applied classify quality. dataset eight significant parameters, but seven parameters considered show values. methodology based on these statistical parameters. Prediction results demonstrated that ANFIS model superior prediction WQI Nevertheless, FFNN achieved highest accuracy (100%) classification (WQC). Furthermore, accurately predicted WQI, showed robustness in classifying WQC. addition, during testing phase, regression coefficient 96.17% This method, using advanced artificial intelligence, aid treatment management.

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ژورنال

عنوان ژورنال: Sustainability

سال: 2021

ISSN: ['2071-1050']

DOI: https://doi.org/10.3390/su13084259