2026-04-27T19:45:58Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/616412023-09-19T19:01:05Zcom_10324_1191com_10324_931com_10324_894col_10324_1379

00925njm 22002777a 4500 dc Rustam, Furqan author Ishaq, Abid author Kokab, Sayyida Tabinda author Torre Díez, Isabel de la author Vidal Mazón, Juan Luis author Rodríguez, Carmen Lili author Ashraf, Imran author 2022 With rapid urbanization, high rates of industrialization, and inappropriate waste disposal, water quality has been substantially degraded during the past decade. So, water quality prediction, an essential element for a healthy society, has become a task of great significance to protecting the water environment. Existing approaches focus predominantly on either water quality or water consumption prediction, utilizing complex algorithms that reduce the accuracy of imbalanced datasets and increase computational complexity. This study proposes a simple architecture of neural networks which is more efficient and accurate and can work for predicting both water quality and water consumption. An artificial neural network (ANN) consisting of one hidden layer and a couple of dropout and activation layers is utilized in this regard. The approach is tested using two datasets for predicting water quality and water consumption. Results show a 0.96 accuracy for water quality prediction which is better than existing studies. A 0.99 R2 score is obtained for water consumption prediction which is superior to existing state-of-the-art approaches. Water, 2022, Vol. 14, Nº. 21, 3359 2073-4441 https://uvadoc.uva.es/handle/10324/61641 10.3390/w14213359 3359 21 Water 14 2073-4441 Water quality Water quality monitoring Agua - Calidad - Control Water consumption Agua - Consumo Water-supply Agua - Abastecimiento Neural networks (Computer science) Redes neuronales (Informática) Classification Artificial intelligence An artificial neural network model for water quality and water consumption prediction