Hydrological time series forecasting is one of the most important applications in modern hydrology, especially for the effective reservoir management. In this research, an artificial neural network (ANN) model coupled with the ensemble empirical mode...
The trophic state index, and in particular, the Carlson Trophic State Index (CTSI), is critical for evaluating reservoir water quality. Despite its common use in evaluating static water quality, the reliability of the CTSI may decrease when water tur...
Groundwater is considered one of the most valuable fresh water resources. The main objective of this study was to produce groundwater spring potential maps in the Koohrang Watershed, Chaharmahal-e-Bakhtiari Province, Iran, using three machine learnin...
Water science and technology : a journal of the International Association on Water Pollution Research
27120649
Because of the importance of water resources management, the need for accurate modeling of the rainfall-runoff process has rapidly grown in the past decades. Recently, the support vector machine (SVM) approach has been used by hydrologists for rainfa...
Computational intelligence and neuroscience
29250110
Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collec...
Inter-basin water transfer projects might cause complex hydro-chemical and biological variation in the receiving aquatic ecosystems. Whether machine learning models can be used to predict changes in phytoplankton community composition caused by water...
Water quality monitoring is a complex issue that requires support tools in order to provide information for water resource management. Budget constraints as well as an inadequate water quality network design call for the development of evaluation too...
Water environment research : a research publication of the Water Environment Federation
29268841
This study analyzes the level of satisfaction of stakeholders in the public participation process (PPP) of water resources management, which is mandatory according to the EU Water Framework Directive (WFD). The methodology uses a fuzzy set/qualitat...
To analyze types and patterns of greening trends across a city, this study seeks to identify a method of creating very high-resolution urban vegetation maps that scales over space and time. Vegetation poses unique challenges for image segmentation be...
International journal of environmental research and public health
32260438
The main aim of this study is to assess groundwater potential of the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) ensemble technique. F...