Deep learning in hydrology and water resources disciplines: Concepts, methods, applications, and research directions
KP Tripathy, AK Mishra - Journal of Hydrology, 2024 - Elsevier
Over the past few years, Deep Learning (DL) methods have garnered substantial
recognition within the field of hydrology and water resources applications. Beginning with a …
recognition within the field of hydrology and water resources applications. Beginning with a …
A review of artificial neural network models for ambient air pollution prediction
Research activity in the field of air pollution forecasting using artificial neural networks
(ANNs) has increased dramatically in recent years. However, the development of ANN …
(ANNs) has increased dramatically in recent years. However, the development of ANN …
[HTML][HTML] The future of sensitivity analysis: an essential discipline for systems modeling and policy support
Sensitivity analysis (SA) is en route to becoming an integral part of mathematical modeling.
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
The tremendous potential benefits of SA are, however, yet to be fully realized, both for …
[HTML][HTML] Exploding the myths: An introduction to artificial neural networks for prediction and forecasting
Abstract Artificial Neural Networks (ANNs), sometimes also called models for deep learning,
are used extensively for the prediction of a range of environmental variables. While the …
are used extensively for the prediction of a range of environmental variables. While the …
Review of surrogate modeling in water resources
Surrogate modeling, also called metamodeling, has evolved and been extensively used
over the past decades. A wide variety of methods and tools have been introduced for …
over the past decades. A wide variety of methods and tools have been introduced for …
Application of ANN technique to predict the performance of solar collector systems-A review
HK Ghritlahre, RK Prasad - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
The solar collector is the heart of any solar energy collection system designed for operation
in the low to medium temperature ranges. So, an efficient design of solar collector system …
in the low to medium temperature ranges. So, an efficient design of solar collector system …
Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions
Over the past 15 years, artificial neural networks (ANNs) have been used increasingly for
prediction and forecasting in water resources and environmental engineering. However …
prediction and forecasting in water resources and environmental engineering. However …
A radial basis function surrogate model assisted evolutionary algorithm for high-dimensional expensive optimization problems
Evolutionary algorithms require large number of function evaluations to locate the global
optimum, making it computationally prohibitive on dealing with expensive problems …
optimum, making it computationally prohibitive on dealing with expensive problems …
A hybrid approach to monthly streamflow forecasting: integrating hydrological model outputs into a Bayesian artificial neural network
Monthly streamflow forecasts are needed to support water resources decision making in the
South East of South Australia, where baseflow represents a significant proportion of the total …
South East of South Australia, where baseflow represents a significant proportion of the total …
Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling
Abstract The application of Artificial Neural Networks (ANNs) in the field of environmental
and water resources modelling has become increasingly popular since early 1990s. Despite …
and water resources modelling has become increasingly popular since early 1990s. Despite …