Comparative analysis of recurrent neural network architectures for reservoir inflow forecasting
Due to the stochastic nature and complexity of flow, as well as the existence of hydrological
uncertainties, predicting streamflow in dam reservoirs, especially in semi-arid and arid …
uncertainties, predicting streamflow in dam reservoirs, especially in semi-arid and arid …
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 …
Streamflow estimation by support vector machine coupled with different methods of time series decomposition in the upper reaches of Yangtze River, China
S Zhu, J Zhou, L Ye, C Meng - Environmental Earth Sciences, 2016 - Springer
Abstract Machine learning models combined with time series decomposition are widely
employed to estimate streamflow, yet the effect of the utilization of different decomposing …
employed to estimate streamflow, yet the effect of the utilization of different decomposing …
A comparative study of artificial neural networks, Bayesian neural networks and adaptive neuro-fuzzy inference system in groundwater level prediction
Predictive modeling of hydrological time series is essential for groundwater resource
development and management. Here, we examined the comparative merits and demerits of …
development and management. Here, we examined the comparative merits and demerits of …
A multivariate streamflow forecasting model by integrating improved complete ensemble empirical mode decomposition with additive noise, sample entropy, Gini …
Accurate and reliable streamflow forecasting is indispensable to deal with the dynamics of
streamflow parameters and for optimal use of water resources, flood, and drought control. In …
streamflow parameters and for optimal use of water resources, flood, and drought control. In …
Potential of kernel and tree-based machine-learning models for estimating missing data of rainfall
In this study, two kernel-based models were used which include Support Vector Regression
(SVR) and Gaussian Process Regression (GPR) and were compared with two tree-based …
(SVR) and Gaussian Process Regression (GPR) and were compared with two tree-based …
Improving flood forecasting in a develo** country: a comparative study of stepwise multiple linear regression and artificial neural network
ZZ Latt, H Wittenberg - Water resources management, 2014 - Springer
Due to limited data sources, practical situations in most develo** countries favor black-box
models in real time operations. In a simple and robust approach, this study examines …
models in real time operations. In a simple and robust approach, this study examines …
Ground water quality classification by decision tree method in Ardebil region, Iran
A decision tree-based approach is proposed to predict ground water quality based on the
United States Salinity Laboratory (USSL) diagram using the data from aquifers in agricultural …
United States Salinity Laboratory (USSL) diagram using the data from aquifers in agricultural …
A hybrid deep learning model based on feature capture of water level influencing factors and prediction error correction for water level prediction of cascade …
X Ma, H Hu, Y Ren - Journal of Hydrology, 2023 - Elsevier
The operating conditions of large cascade hydropower stations are complex. Improving the
water level prediction accuracy of large cascade hydropower stations is significant for flood …
water level prediction accuracy of large cascade hydropower stations is significant for flood …
Rainfall-runoff modeling at **sha River basin by integrated neural network with discrete wavelet transform
Artificial neural network (ANN) models combined with time series decomposition are widely
employed to calculate the river flows; however, the influence of the application of diverse …
employed to calculate the river flows; however, the influence of the application of diverse …