A Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s Parameters: Current Trends and Future Directions

• Published in: Environments (Basel, Switzerland) Vol. 9; no. 7; p. 85
• Main Authors: Khudhair, Zahraa S., Zubaidi, Salah L., Ortega-Martorell, Sandra, Al-Ansari, Nadhir, Ethaib, Saleem, Hashim, Khalid
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2022
• Subjects: Accuracy; Algorithms; Artificial intelligence; Chemical oxygen demand; Data processing; Dissolved oxygen; Forecasting; Freshwater resources; Geoteknik; hybrid model; Internet of Things; Machine learning; Mathematical models; metaheuristic algorithms; Model accuracy; Modelling; Neural networks; Parameters; Prediction models; Rain; Rivers; Soft computing; Soil Mechanics; Support vector machines; Time series; Water quality; water quality parameters

Water quality has a significant influence on human health. As a result, water quality parameter modelling is one of the most challenging problems in the water sector. Therefore, the major factor in choosing an appropriate prediction model is accuracy. This research aims to analyse hybrid techniques...