Theo dơi
Ramendra Prasad
Ramendra Prasad
The University of Fiji
Email được xác minh tại
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition
M Ali, R Prasad
Renewable and Sustainable Energy Reviews 104, 281-295, 2019
Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition
R Prasad, RC Deo, Y Li, T Maraseni
Geoderma 330, 136-161, 2018
Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts
M Ali, R Prasad, Y Xiang, ZM Yaseen
Journal of Hydrology 584, 124647, 2020
Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation
R Prasad, M Ali, P Kwan, H Khan
Applied energy 236, 778-792, 2019
Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm
R Prasad, RC Deo, Y Li, T Maraseni
Atmospheric Research 197, 42-63, 2017
Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach
R Prasad, RC Deo, TN Maraseni, Y Li
Catena 177 (2019), 149-166, 2019
Designing deep-based learning flood forecast model with ConvLSTM hybrid algorithm
M Moishin, RC Deo, R Prasad, N Raj, S Abdulla
IEEE Access 9, 50982-50993, 2021
Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms
M Ali, R Prasad, Y Xiang, RC Deo
Renewable and Sustainable Energy Reviews 132, 110003, 2020
A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms
E Sharma, RC Deo, R Prasad, AV Parisi
Science of the Total Environment 709, 135934, 2020
Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions
H Apaydin, MT Sattari, K Falsafian, R Prasad
Journal of Hydrology 600, 126506, 2021
Comparative analysis of kernel-based versus ANN and deep learning methods in monthly reference evapotranspiration estimation
MT Sattari, H Apaydin, SS Band, A Mosavi, R Prasad
Hydrology and Earth System Sciences 25 (2), 603-618, 2021
Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors
R Prasad, RC Deo, Y Li, T Maraseni
Soil and Tillage Research 181, 63-81, 2018
A double decomposition-based modelling approach to forecast weekly solar radiation
R Prasad, M Ali, Y Xiang, H Khan
Renewable Energy 152, 9-22, 2020
Assessing the sustainable municipal solid waste (MSW) to electricity generation potentials in selected Pacific Small Island Developing States (PSIDS)
LP Joseph, R Prasad
Journal of Cleaner Production 248, 119222, 2020
Deep air quality forecasts: suspended particulate matter modeling with convolutional neural and long short-term memory networks
E Sharma, RC Deo, R Prasad, AV Parisi, N Raj
Ieee Access 8, 209503-209516, 2020
Variational mode decomposition based random forest model for solar radiation forecasting: new emerging machine learning technology
M Ali, R Prasad, Y Xiang, M Khan, AA Farooque, T Zong, ZM Yaseen
Energy Reports 7, 6700-6717, 2021
Near real-time wind speed forecast model with bidirectional LSTM networks
LP Joseph, RC Deo, R Prasad, S Salcedo-Sanz, N Raj, J Soar
Renewable Energy 204, 39-58, 2023
Explainable diabetes classification using hybrid Bayesian-optimized TabNet architecture
LP Joseph, EA Joseph, R Prasad
Computers in Biology and Medicine 151, 106178, 2022
Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots
E Sharma, RC Deo, J Soar, R Prasad, AV Parisi, N Raj
Atmospheric Environment 279, 119111, 2022
Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression …
A Malik, M Jamei, M Ali, R Prasad, M Karbasi, ZM Yaseen
Agricultural Water Management 272, 107812, 2022
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