Potential of artificial intelligence-based techniques for rainfall forecasting in Thailand: A comprehensive review
M Waqas, UW Humphries, A Wangwongchai… - Water, 2023 - mdpi.com
Rainfall forecasting is one of the most challenging factors of weather forecasting all over the
planet. Due to climate change, Thailand has experienced extreme weather events, including …
planet. Due to climate change, Thailand has experienced extreme weather events, including …
Interpretable wind speed prediction with multivariate time series and temporal fusion transformers
Wind power has been utilized well in power systems, so steady and successful wind speed
forecasting is crucial to security management power grid market economy. To date, most …
forecasting is crucial to security management power grid market economy. To date, most …
Wavelet-Seq2Seq-LSTM with attention for time series forecasting of level of dams in hydroelectric power plants
SF Stefenon, LO Seman, LS Aquino… - Energy, 2023 - Elsevier
Reservoir level control in hydroelectric power plants has importance for the stability of the
electric power supply over time and can be used for flood control. In this sense, this paper …
electric power supply over time and can be used for flood control. In this sense, this paper …
An imputation and decomposition algorithms based integrated approach with bidirectional LSTM neural network for wind speed prediction
Due to its renewable and ecological attributes, wind energy is receiving attention on a global
scale. However, exact forecasting of wind speed is challenging owing to its variable and …
scale. However, exact forecasting of wind speed is challenging owing to its variable and …
A simple approach for short-term wind speed interval prediction based on independently recurrent neural networks and error probability distribution
Improving the quality of Wind Speed Interval prediction is important to maximize the usage of
integrated wind energy as well as to reduce the adverse effects of the uncertainties …
integrated wind energy as well as to reduce the adverse effects of the uncertainties …
A robust De-Noising Autoencoder imputation and VMD algorithm based deep learning technique for short-term wind speed prediction ensuring cyber resilience
The intermittent and stochastic characteristics of wind speed make its predictions difficult.
Further, forecasting systems are dependent on the communication network for coordination …
Further, forecasting systems are dependent on the communication network for coordination …
New hybrid approach for short-term wind speed predictions based on preprocessing algorithm and optimization theory
Wind speed predictions are essential for wind power management and wind farm operation.
However, due to the high volatility and nonstationarity of measured wind data, it is often …
However, due to the high volatility and nonstationarity of measured wind data, it is often …
A novel integrated method based on a machine learning model for estimating evapotranspiration in dryland
T Fu, X Li, R Jia, L Feng - Journal of Hydrology, 2021 - Elsevier
Evapotranspiration (ET) plays a vital role in the water cycle and energy cycle and serves as
an important linkage between ecological and hydrological processes. Accurate estimation of …
an important linkage between ecological and hydrological processes. Accurate estimation of …
Short-term probabilistic predictions of wind multi-parameter based on one-dimensional convolutional neural network with attention mechanism and multivariate copula …
Wind speed forecast can effectively guide power grid to schedule adjustable sources to
smooth wind uncertainty and ensure system stability. But due to the limited regulating range …
smooth wind uncertainty and ensure system stability. But due to the limited regulating range …
Interpretable wind speed forecasting with meteorological feature exploring and two-stage decomposition
Wind speed plays a pivotal role in ensuring the stability of power grid operations. However,
the inherent high volatility and non-stationarity of wind patterns pose significant challenges …
the inherent high volatility and non-stationarity of wind patterns pose significant challenges …