Digital water: artificial intelligence and soft computing applications for drinking water quality assessment

[1] Abba SI(2020)Evolutionary computational intelligence algorithm coupled with self-tuning predictive model for water quality index determination J Hydrol 587 2206-2213

[2] Hadi SJ(2022)Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: recent advances and prospects Chem Eng J 427 503-518

[3] Sammen SS(2018)Prediction of water quality parameters using ANFIS optimized by intelligence algorithms (case study: Gorganrood River) KSCE J Civil Eng 22 1797-1819

[4] Salih SQ(2020)A secure fog-based platform for SCADA-based IoT critical infrastructure Softw Practice Experience 50 799-813

[5] Abdulkadir RA(2016)Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran Stoch Environ Res Risk Assess 30 26-35

[6] Pham QB(2018)Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model Stoch Env Res Risk Assess 32 1250013-11

[7] Yaseen ZM(2001)Drinking water quality and treatment: the use of artificial neural networks Can J Civ Eng 28 2-240

[8] Alam G(2012)Performance evaluation of three pattern classification techniques used for water quality monitoring Int J Comput Intell Appl 11 227-244

[9] Ihsanullah I(2002)Optimal division of data for neural network models in water resources applications Water Resour Res 38 229-733

[10] Naushad M(2017)Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management J Environ Manage 201 726-432

[1] Abba SI(2020)Evolutionary computational intelligence algorithm coupled with self-tuning predictive model for water quality index determination J Hydrol 587 2206-2213

[2] Hadi SJ(2022)Applications of artificial intelligence in water treatment for optimization and automation of adsorption processes: recent advances and prospects Chem Eng J 427 503-518

[3] Sammen SS(2018)Prediction of water quality parameters using ANFIS optimized by intelligence algorithms (case study: Gorganrood River) KSCE J Civil Eng 22 1797-1819

[4] Salih SQ(2020)A secure fog-based platform for SCADA-based IoT critical infrastructure Softw Practice Experience 50 799-813

[5] Abdulkadir RA(2016)Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran Stoch Environ Res Risk Assess 30 26-35

[6] Pham QB(2018)Multi-step water quality forecasting using a boosting ensemble multi-wavelet extreme learning machine model Stoch Env Res Risk Assess 32 1250013-11

[7] Yaseen ZM(2001)Drinking water quality and treatment: the use of artificial neural networks Can J Civ Eng 28 2-240

[8] Alam G(2012)Performance evaluation of three pattern classification techniques used for water quality monitoring Int J Comput Intell Appl 11 227-244

[9] Ihsanullah I(2002)Optimal division of data for neural network models in water resources applications Water Resour Res 38 229-733

[10] Naushad M(2017)Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management J Environ Manage 201 726-432