A review of the artificial neural network models for water quality prediction
Water quality prediction plays an important role in environmental monitoring, ecosystem
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
sustainability, and aquaculture. Traditional prediction methods cannot capture the nonlinear …
[HTML][HTML] Impact of deep learning-based dropout on shallow neural networks applied to stream temperature modelling
AP Piotrowski, JJ Napiorkowski, AE Piotrowska - Earth-Science Reviews, 2020 - Elsevier
Although deep learning applicability in various fields of earth sciences is rapidly increasing,
shallow multilayer-perceptron neural networks remain widely used for regression problems …
shallow multilayer-perceptron neural networks remain widely used for regression problems …
Hybrid decision tree-based machine learning models for short-term water quality prediction
Water resources are the foundation of people's life and economic development, and are
closely related to health and the environment. Accurate prediction of water quality is the key …
closely related to health and the environment. Accurate prediction of water quality is the key …
Widespread deoxygenation in warming rivers
Deoxygenation is commonly observed in oceans and lakes but less expected in shallower,
flowing rivers. Here we reconstructed daily water temperature and dissolved oxygen in 580 …
flowing rivers. Here we reconstructed daily water temperature and dissolved oxygen in 580 …
Impact of climate change on river water temperature and dissolved oxygen: Indian riverine thermal regimes
The impact of climate change on the oxygen saturation content of the world's surface waters
is a significant topic for future water quality in a warming environment. While increasing river …
is a significant topic for future water quality in a warming environment. While increasing river …
Exploring the exceptional performance of a deep learning stream temperature model and the value of streamflow data
Stream water temperature (T s) is a variable of critical importance for aquatic ecosystem
health. T s is strongly affected by groundwater-surface water interactions which can be …
health. T s is strongly affected by groundwater-surface water interactions which can be …
Groundwater level modeling using augmented artificial ecosystem optimization
Nature-inspired optimization is an active area of research in the artificial intelligence (AI)
field and has recently been adopted in hydrology for the calibration (training) of both process …
field and has recently been adopted in hydrology for the calibration (training) of both process …
[HTML][HTML] Machine-learning methods for stream water temperature prediction
M Feigl, K Lebiedzinski, M Herrnegger… - Hydrology and Earth …, 2021 - hess.copernicus.org
Water temperature in rivers is a crucial environmental factor with the ability to alter hydro-
ecological as well as socio-economic conditions within a catchment. The development of …
ecological as well as socio-economic conditions within a catchment. The development of …
Forecasting of water level in multiple temperate lakes using machine learning models
Due to global climate change and growing population, fresh water resources are becoming
more vulnerable to pollution. Protecting fresh water resources, especially lakes and the …
more vulnerable to pollution. Protecting fresh water resources, especially lakes and the …
[HTML][HTML] Short-term temperature forecasts using a convolutional neural network—An application to different weather stations in Germany
D Kreuzer, M Munz, S Schlüter - Machine Learning with Applications, 2020 - Elsevier
Local temperature forecasts for horizons up to 24 h are required in many applications. A
common method to generate such forecasts is the Seasonal Autoregressive Integrated …
common method to generate such forecasts is the Seasonal Autoregressive Integrated …