Optimization algorithms as training approach with hybrid deep learning methods to develop an ultraviolet index forecasting model
A. A. Masrur Ahmed(The University of Melbourne), Ambica Sutradhar(Leading University), Oli Ahmed(University of Chittagong), Mohammad Hafez Ahmed(INTI International University), Sanjoy Kanti Saha(Norwegian University of Science and Technology)
Cited by 22
Related Papers
Prediction of dissolved oxygen in Surma River by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks (ANNs)
|Journal of King Saud University - Engineering Sciences|2014|163
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
|Journal of Hydrology|2021|144
Application of adaptive neuro-fuzzy inference system (ANFIS) to estimate the biochemical oxygen demand (BOD) of Surma River
|Journal of King Saud University - Engineering Sciences|2015|134
Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data
|Remote Sensing|2021|95
LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios
|Stochastic Environmental Research and Risk Assessment|2021|73