Abstract
No public abstract is available from the verified source records.
Anto Leoba Jonathan, Dongsheng Cai, Olusola Bamisile, Chiagoziem C. Ukwuoma, Kombou Victor, Joseph Junior Nkou Nkou
Abstract
Authors
Institutions
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Advancing power systems with renewable energy and intelligent technologies: a comprehensive review on grid transformation and integration
2025
Impacts of solar intermittency on future photovoltaic reliability
10.1038/s41467-020-18602-6 · 2020
A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality
10.1016/j.rser.2022.112348 · 2022
Solar irradiance resource and forecasting: a comprehensive review
10.1049/iet-rpg.2019.1227 · 2020
How solar radiation forecasting impacts the utilization of solar energy: a critical review
10.1016/j.jclepro.2023.135860 · 2023
Recent advances in intra-hour solar forecasting: a review of ground-based sky image methods
10.1016/j.ijforecast.2021.11.002 · 2023
Forecasting renewable energy generation with machine learning and deep learning: current advances and future prospects
10.3390/su15097087 · 2023
Unresolved referenced work
2023
Sky type classification for the ISO/CIE Standard General Skies: a proposal for a new approach
10.1093/ijlct/ctab020 · 2021
Provenance
crossref
Confidence 100%
openalex
Confidence 95%
datacite
Confidence 0%
CAELUS: classification of sky conditions from 1-min time series of global solar irradiance using variability indices and dynamic thresholds
10.1016/j.solener.2023.111895 · 2023
An all-sky camera image classification method using cloud cover features
10.5194/amt-15-3629-2022 · 2022
Classification of weather phenomenon from images by using deep convolutional neural network
10.1029/2020ea001604 · 2021
A multimodal deep learning approach for very short-term solar forecasts using sky images and historical numerical data
10.1016/j.renene.2025.123774 · 2025
SKIPP’D: a sky images and photovoltaic power generation dataset for short-term solar forecasting
10.1016/j.solener.2023.03.043 · 2023
Using sky-classification to improve the short-term prediction of irradiance with sky images and convolutional neural networks
10.1016/j.solener.2024.112320 · 2024
A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting
10.1016/j.apenergy.2023.121160 · 2023
Multimodal ultra-short-term probabilistic solar power forecasting with generative AI and Transformer
10.1016/j.adapen.2025.100250 · 2025
Weather phenomena monitoring: optimizing solar irradiance forecasting with temporal fusion transformer
10.1109/access.2024.3517144 · 2024
Solar irradiance forecasting using temporal fusion transformers
10.1155/er/3534500 · 2025
Benchmarking deep learning methods for irradiance estimation from sky images with applications to video prediction-based irradiance nowcasting
10.1016/j.solener.2025.114000 · 2025
Benchmarking of deep learning irradiance forecasting models from sky images – an in-depth analysis
10.1016/j.solener.2021.05.056 · 2021
10.5194/amt-2021-1
10.5194/amt-2021-1
Fast Solar image classification using deep learning and its importance for automation in solar physics
10.1007/s11207-019-1473-z · 2019
Very short-term forecast: different classification methods of the whole sky camera images for sudden PV power variations detection
10.3390/en15249433 · 2022
Short-term solar power prediction learning directly from satellite images with regions of interest
10.1109/tste.2021.3123476 · 2022
Enhancing Sola forecasting accuracy: a fusion of sky images and meteorological data with channel-wise attention
2024
History and trends in solar irradiance and PV power forecasting: a preliminary assessment and review using text mining
10.1016/j.solener.2017.11.023 · 2018
Fractional rectified linear unit activation function and its variants
10.1155/2022/1860779 · 2022
Very short term irradiance forecasting using the lasso
10.1016/j.solener.2015.01.016 · 2015
Self-supervised representation learning: introduction, advances, and challenges
10.1109/msp.2021.3134634 · 2022
Self-supervised learning for solar radio spectrum classification
10.3390/universe8120656 · 2022
Unresolved referenced work
Kept as external metadata until matched
Unresolved referenced work
Kept as external metadata until matched
A modified Adam algorithm for deep neural network optimization
10.1007/s00521-023-08568-z · 2023
Short-term solar irradiance forecasting under data transmission constraints
10.1016/j.renene.2024.121058 · 2024
Photovoltaic nowcasting with Bi-Level spatio-temporal analysis incorporating sky images
10.1109/tste.2021.3064326 · 2021
Photovoltaic nowcasting with Bi-Level spatio-temporal analysis incorporating sky images
10.1109/tste.2021.3064326 · doi-reference
Short-term solar irradiance forecasting under data transmission constraints
10.1016/j.renene.2024.121058 · doi-reference
A modified Adam algorithm for deep neural network optimization
10.1007/s00521-023-08568-z · doi-reference
Self-supervised learning for solar radio spectrum classification
10.3390/universe8120656 · doi-reference
Self-supervised representation learning: introduction, advances, and challenges
10.1109/msp.2021.3134634 · doi-reference
Very short term irradiance forecasting using the lasso
10.1016/j.solener.2015.01.016 · doi-reference
Fractional rectified linear unit activation function and its variants
10.1155/2022/1860779 · doi-reference
History and trends in solar irradiance and PV power forecasting: a preliminary assessment and review using text mining
10.1016/j.solener.2017.11.023 · doi-reference
Short-term solar power prediction learning directly from satellite images with regions of interest
10.1109/tste.2021.3123476 · doi-reference
Very short-term forecast: different classification methods of the whole sky camera images for sudden PV power variations detection
10.3390/en15249433 · doi-reference
Fast Solar image classification using deep learning and its importance for automation in solar physics
10.1007/s11207-019-1473-z · doi-reference
10.5194/amt-2021-1
10.5194/amt-2021-1 · doi-reference
Benchmarking of deep learning irradiance forecasting models from sky images – an in-depth analysis
10.1016/j.solener.2021.05.056 · doi-reference
Benchmarking deep learning methods for irradiance estimation from sky images with applications to video prediction-based irradiance nowcasting
10.1016/j.solener.2025.114000 · doi-reference
Solar irradiance forecasting using temporal fusion transformers
10.1155/er/3534500 · doi-reference
Weather phenomena monitoring: optimizing solar irradiance forecasting with temporal fusion transformer
10.1109/access.2024.3517144 · doi-reference
Multimodal ultra-short-term probabilistic solar power forecasting with generative AI and Transformer
10.1016/j.adapen.2025.100250 · doi-reference
A Transformer-based multimodal-learning framework using sky images for ultra-short-term solar irradiance forecasting
10.1016/j.apenergy.2023.121160 · doi-reference
Using sky-classification to improve the short-term prediction of irradiance with sky images and convolutional neural networks
10.1016/j.solener.2024.112320 · doi-reference
SKIPP’D: a sky images and photovoltaic power generation dataset for short-term solar forecasting
10.1016/j.solener.2023.03.043 · doi-reference
A multimodal deep learning approach for very short-term solar forecasts using sky images and historical numerical data
10.1016/j.renene.2025.123774 · doi-reference
Classification of weather phenomenon from images by using deep convolutional neural network
10.1029/2020ea001604 · doi-reference
An all-sky camera image classification method using cloud cover features
10.5194/amt-15-3629-2022 · doi-reference
CAELUS: classification of sky conditions from 1-min time series of global solar irradiance using variability indices and dynamic thresholds
10.1016/j.solener.2023.111895 · doi-reference
Sky type classification for the ISO/CIE Standard General Skies: a proposal for a new approach
10.1093/ijlct/ctab020 · doi-reference
Forecasting renewable energy generation with machine learning and deep learning: current advances and future prospects
10.3390/su15097087 · doi-reference
Recent advances in intra-hour solar forecasting: a review of ground-based sky image methods
10.1016/j.ijforecast.2021.11.002 · doi-reference
How solar radiation forecasting impacts the utilization of solar energy: a critical review
10.1016/j.jclepro.2023.135860 · doi-reference
Solar irradiance resource and forecasting: a comprehensive review
10.1049/iet-rpg.2019.1227 · doi-reference
A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality
10.1016/j.rser.2022.112348 · doi-reference
Impacts of solar intermittency on future photovoltaic reliability
10.1038/s41467-020-18602-6 · doi-reference