Výsledky vyhledávání - "Mohanad S. Al-Musaylh"

Akademický článek

Integrated Multi-Head Self-Attention Transformer model for electricity demand prediction incorporating local climate variables

Autor: Sujan Ghimire, Thong Nguyen-Huy, Mohanad S. AL-Musaylh, Ravinesh C. Deo, David Casillas-Pérez, Sancho Salcedo-Sanz

Publikováno v: Energy and AI, Vol 14, Iss , Pp 100302- (2023)

This paper develops a trustworthy deep learning model that considers electricity demand (G) and local climate conditions. The model utilises Multi-Head Self-Attention Transformer (TNET) to capture critical information from G, to attain reliable predi

Externí odkaz: https://doaj.org/article/566f7cf083d94a8f914114d375c1b8c2

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Akademický článek

Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results

Autor: Sujan Ghimire, Ravinesh C. Deo, Hua Wang, Mohanad S. Al-Musaylh, David Casillas-Pérez, Sancho Salcedo-Sanz

Publikováno v: Energies, Vol 15, Iss 3, p 1061 (2022)

We review the latest modeling techniques and propose new hybrid SAELSTM framework based on Deep Learning (DL) to construct prediction intervals for daily Global Solar Radiation (GSR) using the Manta Ray Foraging Optimization (MRFO) feature selection

Externí odkaz: https://doaj.org/article/d3d39dc6289f4ba783deca18953921af

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Akademický článek

Electrical Energy Demand Forecasting Model Development and Evaluation with Maximum Overlap Discrete Wavelet Transform-Online Sequential Extreme Learning Machines Algorithms

Autor: Mohanad S. Al-Musaylh, Ravinesh C. Deo, Yan Li

Publikováno v: Energies, Vol 13, Iss 9, p 2307 (2020)

To support regional electricity markets, accurate and reliable energy demand (G) forecast models are vital stratagems for stakeholders in this sector. An online sequential extreme learning machine (OS-ELM) model integrated with a maximum overlap disc

Externí odkaz: https://doaj.org/article/925404e2042e450cb159cf605d7fc758

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Forecasting solar photosynthetic photon flux density under cloud cover effects: novel predictive model using convolutional neural network integrated with long short-term memory network

Autor: Ravinesh C. Deo, Richard H. Grant, Ann Webb, Sujan Ghimire, Damien P. Igoe, Nathan J. Downs, Mohanad S. Al-Musaylh, Alfio V. Parisi, Jeffrey Soar

Publikováno v: Stochastic Environmental Research and Risk Assessment. 36:3183-3220

Forecast models of solar radiation incorporating cloud effects are useful tools to evaluate the impact of stochastic behaviour of cloud movement, real-time integration of photovoltaic energy in power grids, skin cancer and eye disease risk minimisati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9016814cbd64ba740d8f3772a09646ab
https://doi.org/10.1007/s00477-022-02188-0

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Multi-step solar UV index prediction using deep learning methods

Autor: Mohanad S Al-Musaylh, Sujan Ghimire, Kadhem Al-Daffaie, Mumtaz Ali, Ravinesh C Deo, Nathan Downs, Damien P. Igoe, Alfio V Parisi

The impact of ultraviolet (UV) radiation on public health is severe and can cause sunburn, skin aging and cancer, immunosuppression, and eye damage. Minimization of exposure to solar UV is required in order to reduce the risks of these illnesses to t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d40a0bedd011202e6deaad4c283fbcba
https://doi.org/10.21203/rs.3.rs-2449044/v1

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Gas consumption demand forecasting with empirical wavelet transform based machine learning model: A case study

Autor: Kadhem Al-Daffaie, Mohanad S. AL‐Musaylh, Ramendra Prasad

Publikováno v: International Journal of Energy Research. 45:15124-15138

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::c82f9cc426c21f2f42a84c8c7c762145
https://doi.org/10.1002/er.6788

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Akademický článek

Particle Swarm Optimized–Support Vector Regression Hybrid Model for Daily Horizon Electricity Demand Forecasting Using Climate Dataset

Autor: Mohanad S AL-Musaylh, Ravinesh C Deo, Yan Li

Publikováno v: E3S Web of Conferences, Vol 64, p 08001 (2018)

This paper has adopted six daily climate variables for the eleven major locations, and heavily populated areas in Queensland, Australia obtained from Scientific Information for Land Owners (SILO) to forecast the daily electricity demand (G) obtained

Externí odkaz: https://doaj.org/article/f36b95e326824ae9b9ce45af588c80dc

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Forecasting Photosynthetic Photon Flux Density Under Cloud Effects: Novel Predictive Model Using Convolutional Neural Network Integrated With Long Short-term Memory Network

Autor: Nathan Downs, Sujan Ghimire, Ann Webb, Damien P. Igoe, Jeffrey Soar, Mohanad S. Al-Musaylh, Ravinesh C. Deo, Alfio V. Parisi, Richard H Grant

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::823a8f5dc241689caa8f9b05d961902a
https://doi.org/10.21203/rs.3.rs-1069113/v1

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Autor: Raid Luaibi Lafta, Mohanad S. AL-Musaylh, Qahtan Makki Shallal

Publikováno v: Indonesian Journal of Electrical Engineering and Computer Science. 26:947

Developed intelligent technologies are become play a promising role in providing better decision-making and improving the medical services provided to the patients. A risk prediction task for short-term is big challenge task; however, it is a great i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aaace9e84788672e7c2aecb68560fa3f
https://doi.org/10.11591/ijeecs.v26.i2.pp947-954

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