Theo dơi
Mohanad S AL-Musaylh
Mohanad S AL-Musaylh
Southern Technical University
Email được xác minh tại stu.edu.iq
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
MS Al-Musaylh, RC Deo, JF Adamowski, Y Li
Advanced Engineering Informatics 35, 1-16, 2018
2872018
Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon …
MS Al-Musaylh, RC Deo, Y Li, JF Adamowski
Applied energy 217, 422-439, 2018
1372018
Stacked LSTM sequence-to-sequence autoencoder with feature selection for daily solar radiation prediction: a review and new modeling results
S Ghimire, RC Deo, H Wang, MS Al-Musaylh, D Casillas-Pérez, ...
Energies 15 (3), 1061, 2022
622022
Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF Reanalysis atmospheric predictors in southeast Queensland …
MS Al-Musaylh, RC Deo, JF Adamowski, Y Li
Renewable and Sustainable Energy Reviews 113, 109293, 2019
562019
Electrical energy demand forecasting model development and evaluation with maximum overlap discrete wavelet transform-online sequential extreme learning machines algorithms
MS Al-Musaylh, RC Deo, Y Li
Energies 13 (9), 2307, 2020
292020
A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction
S Ghimire, T Nguyen-Huy, MS AL-Musaylh, RC Deo, D Casillas-Pérez, ...
Energy 275, 127430, 2023
222023
Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory …
RC Deo, RH Grant, A Webb, S Ghimire, DP Igoe, NJ Downs, ...
Stochastic Environmental Research and Risk Assessment 36 (10), 3183-3220, 2022
132022
Gas consumption demand forecasting with empirical wavelet transform based machine learning model: A case study
MS AL‐Musaylh, K Al‐Daffaie, R Prasad
International Journal of Energy Research 45 (10), 15124-15138, 2021
112021
Particle swarm optimized–support vector regression hybrid model for daily horizon electricity demand forecasting using climate dataset
SALM Mohanad, CD Ravinesh, L Yan
E3S web of conferences 64, 08001, 2018
112018
Hybrid deep learning model for wave height prediction in Australia's wave energy region
AAM Ahmed, SJJ Jui, MS AL-Musaylh, N Raj, R Saha, RC Deo, SK Saha
Applied Soft Computing 150, 111003, 2024
72024
Advanced engineering informatics short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
MS Al-Musaylh, RC Deo, JF Adamowski, Y Li
Advanced Engineering Informatics 35, 1-16, 2018
52018
Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables
S Ghimire, T Nguyen-Huy, MS AL-Musaylh, RC Deo, D Casillas-Pérez, ...
Energy and AI 14, 100302, 2023
32023
Multi-step solar UV index prediction using deep learning methods
MS Al-Musaylh, S Ghimire, K Al-Daffaie, M Ali, RC Deo, N Downs, ...
22023
Clustering similar time series data for the prediction the patients with heart disease
RL Lafta, MS AL-Musaylh, QM Shallal
Indonesian Journal of Electrical Engineering and Computer Science 26 (2), 947, 2022
22022
Forecasting photosynthetic photon flux density under cloud effects: Novel predictive model using convolutional neural network integrated with long short-term memory network
RC Deo, RH Grant, A Webb, S Ghimire, DP Igoe, NJ Downs, ...
22021
On the existence and the nonexistence of some (𝐤, 𝐧)− arcs in 𝐏𝐆 (𝟐, 𝟑𝟕)
MS Khalid
Journal of Basrah Researches ((Sciences)) 39 (2), 2013
12013
Development of data intelligent models for electricity demand forecasting: case studies in the state of Queensland, Australia
MSK Al-Musaylh
University of Southern Queensland, 2020
2020
On the existence and the nonexistence of some (𝐤, 𝐧)− arcs in 𝐏𝐆 (𝟐, 𝟑𝟕)
MS Khalid
Journal of Basrah Researches ((Sciences)) 39 (2), 2013
2013
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Bài viết 1–18