Prediction of the five-day biochemical oxygen demand and chemical oxygen demand in natural streams using machine learning methods

Rivers, as the most prominent component of water resources, have a key role to play in increasing the life expectancy of living creatures. The essential characteristics of water pollutants can be described by water quality indices (WQIs). Hence, a ferocious demand for obtaining an accurate predictio...

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Bibliographic Details
Published in:	Environmental monitoring and assessment Vol. 191; no. 6; pp. 380 - 21
Main Authors:	Najafzadeh, Mohammad, Ghaemi, Alireza
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 01-06-2019 Springer Nature B.V
Subjects:	Adaptive systems Artificial intelligence Artificial neural networks Atmospheric Protection/Air Quality Control/Air Pollution Biochemical oxygen demand Biological Oxygen Demand Analysis Calcium Calcium ions Chemical oxygen demand Creeks & streams Earth and Environmental Science Ecology Ecotoxicology Electrical conductivity Electrical resistivity Environment Environmental Management Environmental monitoring Environmental Monitoring - methods Environmental science Fuzzy logic Fuzzy systems Iran Learning algorithms Learning theory Life expectancy Life span Machine Learning Magnesium Mathematical models Monitoring/Environmental Analysis Multivariate Analysis Natural streams Neural networks Neural Networks (Computer) Nitrates Nitrogen dioxide Organic chemistry Orthophosphate Oxygen Parameters Pollutants Regression Analysis Rivers Rivers - chemistry Sodium Statistical analysis Streams Support Vector Machine Support vector machines Total oxygen demand Training Turbidity Water Pollutants - analysis Water pollution Water quality Water Quality - standards Water resources Iran River pollution Water quality indices Multiple regression-based equations Multivariate adaptive regression spline Least square-support vector machine Statistical criteria
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