A comprehensive review of artificial intelligence-based methods for predicting pan evaporation rate
This comprehensive study reviews the latest and most popular artificial intelligence (AI)
techniques utilised for estimating pan evaporation (Ep), an essential parameter for water …
techniques utilised for estimating pan evaporation (Ep), an essential parameter for water …
[HTML][HTML] Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Recently, numerous forecasting models have been reported in the wind power forecasting
field, aiming for reliable integration of renewable energy into the electric grid. Decomposition …
field, aiming for reliable integration of renewable energy into the electric grid. Decomposition …
Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data
RM Adnan, RR Mostafa, HL Dai… - Engineering …, 2023 - Taylor & Francis
This study investigates the feasibility of a relevance vector machine tuned with improved
Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using …
Manta-Ray foraging optimization (RVM-IMRFO) in predicting monthly pan evaporation using …
Multiscale groundwater level forecasting: Coupling new machine learning approaches with wavelet transforms
Groundwater level (GWL) forecasting is crucial for irrigation scheduling, water supply and
land development. Machine learning (ML)(eg, artificial neural networks) has been …
land development. Machine learning (ML)(eg, artificial neural networks) has been …
[HTML][HTML] Energy consumption and economic growth in Italy: A wavelet analysis
This paper investigates the relationship between energy consumption and economic growth
with over eighty decades of Italian dataset. The wavelet analysis is applied to decompose …
with over eighty decades of Italian dataset. The wavelet analysis is applied to decompose …
Forecasting of particulate matter with a hybrid ARIMA model based on wavelet transformation and seasonal adjustment
E Aladağ - Urban Climate, 2021 - Elsevier
Particulate matter is one of the primary atmospheric pollutants with significant effects on
human health. Accurately and reliably forecasting air quality for future horizons makes it …
human health. Accurately and reliably forecasting air quality for future horizons makes it …
On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective–A comprehensive assessment of data analysis techniques
The main aim of the present study is to investigate the capabilities of four robust machine
learning method-the Kernel Extreme Learning Machine (KELM), Adaptive Regression …
learning method-the Kernel Extreme Learning Machine (KELM), Adaptive Regression …
Efficient metaheuristic-retrofitted techniques for concrete slump simulation
Due to the benefits of the early prediction of concrete slump, introducing an efficient model
for this purpose is of great importance. Considering this motivation, four strong metaheuristic …
for this purpose is of great importance. Considering this motivation, four strong metaheuristic …
A wavelet-particle swarm optimization-extreme learning machine hybrid modeling for significant wave height prediction
Predictions of Significant wave height (Hs) of oceans is highly required in advance for
coastal and ocean engineering applications. Therefore, this study aims to precisely predict …
coastal and ocean engineering applications. Therefore, this study aims to precisely predict …
An adaptive daily runoff forecast model using VMD-LSTM-PSO hybrid approach
X Wang, Y Wang, P Yuan, L Wang… - Hydrological Sciences …, 2021 - Taylor & Francis
To cope with the nonlinear and nonstationarity challenges faced by conventional runoff
forecasting models and improve daily runoff prediction accuracy, a hybrid model-based …
forecasting models and improve daily runoff prediction accuracy, a hybrid model-based …