Applications of hybrid wavelet–artificial intelligence models in hydrology: a review
Accurate and reliable water resources planning and management to ensure sustainable use
of watershed resources cannot be achieved without precise and reliable models …
of watershed resources cannot be achieved without precise and reliable models …
Employing machine learning algorithms for streamflow prediction: a case study of four river basins with different climatic zones in the United States
Streamflow estimation plays a significant role in water resources management, especially for
flood mitigation, drought warning, and reservoir operation. Hence, the current study …
flood mitigation, drought warning, and reservoir operation. Hence, the current study …
Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions
The nature of streamflow in the basins is stochastic and complex making it difficult to make
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
A drought forecasting model is a practical tool for drought-risk management. Drought models
are used to forecast drought indices (DIs) that quantify drought by its onset, termination, and …
are used to forecast drought indices (DIs) that quantify drought by its onset, termination, and …
A comparative study of MLR, KNN, ANN and ANFIS models with wavelet transform in monthly stream flow prediction
A Khazaee Poul, M Shourian, H Ebrahimi - Water Resources Management, 2019 - Springer
Reliable and precise prediction of the rivers flow is a major concern in hydrologic and water
resources analysis. In this study, multi-linear regression (MLR) as a statistical method …
resources analysis. In this study, multi-linear regression (MLR) as a statistical method …
Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran
Abstract The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference
System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels …
System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels …
Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural network
Data-driven models have been widely developed and achieved impressive results in
streamflow prediction. However, the existing data-driven models mostly focus on the …
streamflow prediction. However, the existing data-driven models mostly focus on the …
Coupling machine learning methods with wavelet transforms and the bootstrap and boosting ensemble approaches for drought prediction
This study explored the ability of coupled machine learning models and ensemble
techniques to predict drought conditions in the Awash River Basin of Ethiopia. The potential …
techniques to predict drought conditions in the Awash River Basin of Ethiopia. The potential …
Evaluation of data driven models for river suspended sediment concentration modeling
Using eight-year data series from hydrometric stations located in Arkansas, Delaware and
Idaho (USA), the ability of artificial neural network (ANN) and support vector regression …
Idaho (USA), the ability of artificial neural network (ANN) and support vector regression …
Evaluation of random forests for short-term daily streamflow forecasting in rainfall-and snowmelt-driven watersheds
In the past decades, data-driven machine-learning (ML) models have emerged as promising
tools for short-term streamflow forecasting. Among other qualities, the popularity of ML …
tools for short-term streamflow forecasting. Among other qualities, the popularity of ML …