On the public citation graph

Machine Learning Based Photovoltaics (PV) Power Prediction Using Different Environmental Parameters of Qatar

0 signed · 217 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf01060893openalex-snapshot
Some suggestions for measuring predictive performance
inferredcites →https://doi.org/10.1007/s10668-016-9875-7openalex-snapshot
Experimental investigation of dust pollutants and the impact of environmental parameters on PV performance: an experimental study
inferredcites →https://doi.org/10.1016/j.fcij.2017.02.001openalex-snapshot
A survey of IoT cloud platforms
inferredcites →https://doi.org/10.1016/j.jclepro.2017.12.065openalex-snapshot
Prediction of hourly solar radiation in Abu Musa Island using machine learning algorithms
inferredcites →https://doi.org/10.1016/j.jksues.2014.03.007openalex-snapshot
Future of solar energy in Saudi Arabia
inferredcites →https://doi.org/10.1016/j.renene.2015.12.046openalex-snapshot
Investigation of solar PV performance under Doha weather using a customized measurement and monitoring system
inferredcites →https://doi.org/10.1016/j.renene.2015.12.069openalex-snapshot
Machine learning for solar irradiance forecasting of photovoltaic system
inferredcites →https://doi.org/10.1016/j.renene.2017.06.078openalex-snapshot
Long-term performance analysis and power prediction of PV technology in the State of Qatar
inferredcites →https://doi.org/10.1016/j.solener.2010.02.006openalex-snapshot
A 24-h forecast of solar irradiance using artificial neural network: Application for performance prediction of a grid-connected PV plant at Trieste, Italy
inferredcites →https://doi.org/10.1016/j.solener.2014.05.030openalex-snapshot
Energy yield loss caused by dust deposition on photovoltaic panels
inferredcites →https://doi.org/10.1063/1.4823194openalex-snapshot
Data Reduction and Error Analysis for the Physical Sciences
inferredcites →https://doi.org/10.1109/iccons.2018.8663110openalex-snapshot
Predicting Solar Radiation Using Machine Learning Techniques
inferredcites →https://doi.org/10.1109/ictai.2009.20openalex-snapshot
High-Dimensional Software Engineering Data and Feature Selection
inferredcites →https://doi.org/10.1109/intech.2016.7845051openalex-snapshot
Predicting daily mean solar power using machine learning regression techniques
inferredcites →https://doi.org/10.1109/ipecon.2010.5697002openalex-snapshot
Investigation of ANN performance for tracking the optimum points of PV module under partially shaded conditions
inferredcites →https://doi.org/10.1109/is.2006.348488openalex-snapshot
Artificial intelligence based-modeling for sizing of a Stand-Alone Photovoltaic Power System: Proposition for a New Model using Neuro-Fuzzy System (ANFIS)
inferredcites →https://doi.org/10.1109/jphotov.2014.2368711openalex-snapshot
Approaches for Developing a Regression Model for Sizing a Stand-Alone Photovoltaic System
inferredcites →https://doi.org/10.1109/pcitc.2015.7438155openalex-snapshot
Short term wind power forecasting using Chebyshev polynomial trained by ridge extreme learning machine
inferredcites →https://doi.org/10.1109/pesgm.2012.6345222openalex-snapshot
Short Term Load Forecasting improved by ensemble and its variations
inferredcites →https://doi.org/10.1109/tie.2017.2714127openalex-snapshot
Short-Term Solar Power Forecasting Based on Weighted Gaussian Process Regression
inferredcites →https://doi.org/10.1109/tpec.2018.8312085openalex-snapshot
An aggregative machine learning approach for output power prediction of wind turbines
inferredcites →https://doi.org/10.1142/6986openalex-snapshot
Linear Regression Analysis
inferredcites →https://doi.org/10.1155/2014/569249openalex-snapshot
A Novel Hybrid Model for Short-Term Forecasting in PV Power Generation
inferredcites →https://doi.org/10.1155/2017/2437387openalex-snapshot
Feature Selection and ANN Solar Power Prediction
inferredcites →https://doi.org/10.11591/ijpeds.v9.i3.pp1356-1366openalex-snapshot
Effect of dust accumulation on the performance of photovoltaic panels in desert countries: A case study for Madinah, Saudi Arabia
inferredcites →https://doi.org/10.1162/neco.1992.4.3.415openalex-snapshot
Bayesian Interpolation
inferredcites →https://doi.org/10.2172/919131openalex-snapshot
Photovoltaic array performance model.
inferredcites →https://doi.org/10.3390/en11113231openalex-snapshot
Novel Design for Thermal Management of PV Cells in Harsh Environmental Conditions
inferredcites →https://doi.org/10.4067/s0718-58392010000300010openalex-snapshot
Comparison of Regression and Neural Networks Models to Estimate Solar Radiation
inferredcites →https://doi.org/10.5339/qfarc.2016.eepp2538openalex-snapshot
Outdoor Testing in Qatar of PV Performance, Reliability and Safety
inferredcites →https://doi.org/10.5555/944919.944968openalex-snapshot
An introduction to variable and feature selection
inferredcites →https://doi.org/10.5860/choice.41-5949openalex-snapshot
Information theory, inference, and learning algorithms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4610914openalex-extracted
Assessment of Electrical and Thermal Efficiency of Nanofluid-Based Photovoltaic Thermal Solar Collectors by Advanced Machine Learning Models
inferred← citeshttps://doi.org/10.2139/ssrn.4905242openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-3-030-72322-4_71-1openalex-snapshot
Applications of Machine Learning for Renewable Energy: Issues, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1007/978-3-030-89554-9_12openalex-snapshot
A Review of Machine Learning Models in Renewable Energy
inferred← citeshttps://doi.org/10.1007/978-3-030-97940-9_71openalex-snapshot
Applications of Machine Learning for Renewable Energy: Issues, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1007/978-3-031-20398-5_12openalex-snapshot
Critical Feature Selection and Machine Learning-based Models for Monofacial and Bifacial Photovoltaics
inferred← citeshttps://doi.org/10.1007/978-3-031-40725-3_49openalex-snapshot
Daily Accumulative Photovoltaic Energy Prediction Using Hybrid Intelligent Model
inferred← citeshttps://doi.org/10.1007/978-3-031-50920-9_16openalex-snapshot
PV Output Power Prediction Using Regression Methods
inferred← citeshttps://doi.org/10.1007/978-3-031-94788-9_26openalex-snapshot
Prediction of the Output Power of Two-Axis Tracking Grid-Connected Photovoltaic System Located in 25 Selected Coastal Mediterranean Cities
inferred← citeshttps://doi.org/10.1007/978-3-032-16883-2_49openalex-snapshot
Machine Learning-Based Prediction of Hourly Solar PV Power Generation: A Case Study in Al Mahmra, Lebanon
inferred← citeshttps://doi.org/10.1007/978-981-96-0644-3_51openalex-snapshot
Comparative Analysis of Machine Learning Models for Predicting CdTe PV Module Performance in Semi-arid Climate
inferred← citeshttps://doi.org/10.1007/978-981-99-8135-9_15openalex-snapshot
Unveiling Worldwide Prospects and Challenges in Implementing Telematics Technologies in Electric Vehicles
inferred← citeshttps://doi.org/10.1007/978-981-99-8937-9_45openalex-snapshot
Improving Solar Panel Efficiency: A CNN-Based System for Dust Detection and Maintenance
inferred← citeshttps://doi.org/10.1007/s00202-024-02759-0openalex-snapshot
A review of the state of the art in solar photovoltaic output power forecasting using data-driven models
inferred← citeshttps://doi.org/10.1007/s00521-025-11058-zopenalex-snapshot
A next-generation hybrid energy converter empowered by machine learning: pioneering sustainable integration of photovoltaic and grid power
inferred← citeshttps://doi.org/10.1007/s11227-024-06504-zopenalex-snapshot
Innovative approaches to solar energy forecasting: unveiling the power of hybrid models and machine learning algorithms for photovoltaic power optimization
inferred← citeshttps://doi.org/10.1007/s13762-023-05110-5openalex-snapshot
Solar panel energy production forecasting by machine learning methods and contribution of lifespan to sustainability
inferred← citeshttps://doi.org/10.1007/s13762-026-07075-7openalex-snapshot
Removal of alizarin yellow GG by K2Al2B2O7: modeling with artificial neural networks (ANNs)
inferred← citeshttps://doi.org/10.1007/s40808-022-01413-7openalex-snapshot
Selection of most relevant input parameters for predicting photovoltaic output power using machine learning and quadratic models
inferred← citeshttps://doi.org/10.1016/b978-0-443-36459-4.00016-6openalex-snapshot
Emerging trends: Artificial intelligence, deep learning, big data, and the role of digital twins applied to energy communities
inferred← citeshttps://doi.org/10.1016/j.aej.2024.03.049openalex-snapshot
Energy and economic analysis of building integrated photovoltaic thermal system: Seasonal dynamic modeling assisted with machine learning-aided method and multi-objective genetic optimization
inferred← citeshttps://doi.org/10.1016/j.apenergy.2021.116817openalex-snapshot
Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales
inferred← citeshttps://doi.org/10.1016/j.apenergy.2022.119848openalex-snapshot
Two-Stage stochastic optimization for operating a Renewable-Based Microgrid
inferred← citeshttps://doi.org/10.1016/j.apenergy.2024.122858openalex-snapshot
A novel SARCIMA model based on central difference and its application in solar power generation of China
inferred← citeshttps://doi.org/10.1016/j.apenergy.2025.126016openalex-snapshot
A review of solar and wind energy forecasting: From single-site to multi-site paradigm
inferred← citeshttps://doi.org/10.1016/j.applthermaleng.2024.123029openalex-snapshot
Optimizing photovoltaic thermal solar systems efficiency through advanced artificial intelligence driven thermal management techniques
inferred← citeshttps://doi.org/10.1016/j.asej.2024.102716openalex-snapshot
On reliability enhancement of solar PV arrays using hybrid SVR for soiling forecasting based on WT and EMD decomposition methods
inferred← citeshttps://doi.org/10.1016/j.compchemeng.2022.107925openalex-snapshot
Challenges and opportunities in carbon capture, utilization and storage: A process systems engineering perspective
inferred← citeshttps://doi.org/10.1016/j.compeleceng.2026.111075openalex-snapshot
Novel incremental machine learning approach for predicting photovoltaic power in systems with hydrophobic coating
inferred← citeshttps://doi.org/10.1016/j.compstruct.2020.112654openalex-snapshot
Optimal filler content for cotton fiber/PP composite based on mechanical properties using artificial neural network
inferred← citeshttps://doi.org/10.1016/j.compstruct.2020.112885openalex-snapshot
Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
inferred← citeshttps://doi.org/10.1016/j.compstruct.2020.113207openalex-snapshot
Data-driven modeling to predict the load vs. displacement curves of targeted composite materials for industry 4.0 and smart manufacturing
inferred← citeshttps://doi.org/10.1016/j.compstruct.2021.114858openalex-snapshot
Design of composite rectangular tubes for optimum crashworthiness performance via experimental and ANN techniques
inferred← citeshttps://doi.org/10.1016/j.csite.2024.104459openalex-snapshot
Advancing solar PV panel power prediction: A comparative machine learning approach in fluctuating environmental conditions
inferred← citeshttps://doi.org/10.1016/j.egyai.2022.100182openalex-snapshot
Artificial intelligence in renewable systems for transformation towards intelligent buildings
inferred← citeshttps://doi.org/10.1016/j.egyr.2021.11.252openalex-snapshot
Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm
inferred← citeshttps://doi.org/10.1016/j.egyr.2023.05.063openalex-snapshot
Renewables integration into power systems through intelligent techniques: Implementation procedures, key features, and performance evaluation
inferred← citeshttps://doi.org/10.1016/j.egyr.2023.05.229openalex-snapshot
Deep hybrid neural net (DHN-Net) for minute-level day-ahead solar and wind power forecast in a decarbonized power system
inferred← citeshttps://doi.org/10.1016/j.egyr.2023.09.097openalex-snapshot
Predictive modeling of PV solar power plant efficiency considering weather conditions: A comparative analysis of artificial neural networks and multiple linear regression
inferred← citeshttps://doi.org/10.1016/j.egyr.2023.12.031openalex-snapshot
Unveiling the backbone of the renewable energy forecasting process: Exploring direct and indirect methods and their applications
inferred← citeshttps://doi.org/10.1016/j.egyr.2024.08.041openalex-snapshot
Innovative hybrid NARX-RNN model for predicting wind speed to harness wind power in Pakistan
inferred← citeshttps://doi.org/10.1016/j.egyr.2026.109332openalex-snapshot
Renewable energy forecasting: Engineering foundations, AI-driven approaches, current challenges, and future research directions
inferred← citeshttps://doi.org/10.1016/j.enconman.2022.115790openalex-snapshot
Application of nanofluid in solar energy harvesting devices: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.energy.2025.135764openalex-snapshot
Prediction of photovoltaic panel cell temperatures: Application of empirical and machine learning models
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.108155openalex-snapshot
A new Takagi–Sugeno–Kang model for time series forecasting
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e26088openalex-snapshot
Renewable energy sources integration via machine learning modelling: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.ijepes.2020.106461openalex-snapshot
Machine learning based weighted scheduling scheme for active power control of hybrid microgrid
inferred← citeshttps://doi.org/10.1016/j.ijepes.2025.110866openalex-snapshot
Long-term comparative analysis of machine learning models: A deep dive into applications of artificial intelligence for enhancing photovoltaic performance prediction
inferred← citeshttps://doi.org/10.1016/j.jag.2025.104786openalex-snapshot
GeoAI-Driven mapping of urban rooftop Photovoltaics: A sustainable energy framework for Karachi, Pakistan
inferred← citeshttps://doi.org/10.1016/j.jclepro.2022.132701openalex-snapshot
Using machine learning in photovoltaics to create smarter and cleaner energy generation systems: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.jclepro.2023.139015openalex-snapshot
Analyzing the effect of normally distributed cooling channels on a photovoltaic thermal solar unit
inferred← citeshttps://doi.org/10.1016/j.jcomc.2024.100440openalex-snapshot
Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network
inferred← citeshttps://doi.org/10.1016/j.jestch.2024.101874openalex-snapshot
A green hydrogen production model from solar powered water electrolyze based on deep chaotic Lévy gazelle optimization
inferred← citeshttps://doi.org/10.1016/j.jobe.2025.114117openalex-snapshot
Machine learning for power forecasting in BIPV and BAPV Systems: A review
inferred← citeshttps://doi.org/10.1016/j.mtcomm.2023.107318openalex-snapshot
Prediction of band gap and optimum electrical parameters of a thin homojunction perovskite solar cell based on FA1−xCsxSnyPb1−yI3 through a combination of SCAPS-1D and machine learning based modelling
inferred← citeshttps://doi.org/10.1016/j.neucom.2023.01.006openalex-snapshot
Machine learning applications for urban photovoltaic potential estimation: A survey
inferred← citeshttps://doi.org/10.1016/j.nexus.2026.100749openalex-snapshot
Digitalization of solar PV systems in the GCC countries: A comprehensive review on AI and IoT-driven approaches
inferred← citeshttps://doi.org/10.1016/j.nxmate.2026.101968openalex-snapshot
Forecasting and techno-economic optimization of residential PV-battery systems: A synergistic approach for system enhancement
inferred← citeshttps://doi.org/10.1016/j.nxmate.2026.102275openalex-snapshot
Comparison of RSM and ANN prediction approaches for crystal violet removal by Fe-modified Cedrus libani carpel biochar
inferred← citeshttps://doi.org/10.1016/j.procs.2024.05.007openalex-snapshot
Prediction of energy production in a building-integrated photovoltaic system using machine learning algorithms
inferred← citeshttps://doi.org/10.1016/j.ref.2025.100739openalex-snapshot
A review of data-driven deep learning models for solar and wind energy forecasting
inferred← citeshttps://doi.org/10.1016/j.renene.2021.04.103openalex-snapshot
Approximation of photovoltaic characteristics curves using Bézier Curve
inferred← citeshttps://doi.org/10.1016/j.renene.2024.122149openalex-snapshot
Predictive modeling of photovoltaic system cleaning schedules using machine learning techniques
inferred← citeshttps://doi.org/10.1016/j.renene.2025.123685openalex-snapshot
A machine learning approach to PV-climate classification
inferred← citeshttps://doi.org/10.1016/j.rineng.2024.103838openalex-snapshot
Advanced automated machine learning framework for photovoltaic power output prediction using environmental parameters and SHAP interpretability
inferred← citeshttps://doi.org/10.1016/j.rineng.2026.112840openalex-snapshot
Fractional-order modeling of climate-driven thermo-hygro-corrosion effects in photovoltaic modules using an electrical degradation proxy
inferred← citeshttps://doi.org/10.1016/j.scsadv.2026.100088openalex-snapshot
Mapping the research landscape of artificial intelligence and optimization for solar photovoltaic power systems: a bibliometric analysis
inferred← citeshttps://doi.org/10.1016/j.seta.2021.101360openalex-snapshot
Advances in PV and PVT cooling technologies: A review
inferred← citeshttps://doi.org/10.1016/j.suscom.2024.100960openalex-snapshot
PV parameters estimation using optimized deep neural networks
inferred← citeshttps://doi.org/10.1016/j.susmat.2024.e00863openalex-snapshot
Development of a stacked machine learning model to compute the capability of ZnO-based sensors for hydrogen detection
inferred← citeshttps://doi.org/10.1021/acsomega.6c01622openalex-snapshot
Multiscale Modeling of Quantum Dot Solar Cells: Integration of Density Functional Theory, SCAPS, Lambert W Analysis, and Machine Learning
inferred← citeshttps://doi.org/10.1038/s44406-026-00038-4openalex-snapshot
Quantifying drivers of photovoltaic power generation at Bhadla using explainable machine learning and causal discovery
inferred← citeshttps://doi.org/10.1049/iet-rpg.2020.0351openalex-snapshot
Systematic literature review of photovoltaic output power forecasting
inferred← citeshttps://doi.org/10.1051/e3sconf/202235402004openalex-snapshot
Real time photovoltaic power forecasting and modelling using machine learning techniques
inferred← citeshttps://doi.org/10.1051/e3sconf/202454702002openalex-snapshot
IOT Based Automated Indoor Hydroponic Farming System
inferred← citeshttps://doi.org/10.1080/01430750.2022.2063384openalex-snapshot
A review of artificial intelligence applied for the solution of issues in the extensive adaption of solar and wind energy
inferred← citeshttps://doi.org/10.1080/01430750.2023.2276127openalex-snapshot
Experimentally investigated machine learning based MPPT for PV panel systems
inferred← citeshttps://doi.org/10.1080/02533839.2023.2238777openalex-snapshot
An ensemble machine learning-based solar power prediction of meteorological variability conditions to improve accuracy in forecasting
inferred← citeshttps://doi.org/10.1080/02626667.2025.2530124openalex-snapshot
Uncovering the underlying drivers of West African monsoon variability: towards the development of efficient rainfall monitoring systems
inferred← citeshttps://doi.org/10.1080/15567036.2021.1921886openalex-snapshot
Novel Python-based “ all-regressor model ” application for photovoltaic plant-specific yield estimation and systematic analysis
inferred← citeshttps://doi.org/10.1080/19942060.2022.2126528openalex-snapshot
Investigating photovoltaic solar power output forecasting using machine learning algorithms
inferred← citeshttps://doi.org/10.1088/1361-6579/ac1d59openalex-snapshot
Deep learning based classification of unsegmented phonocardiogram spectrograms leveraging transfer learning
inferred← citeshttps://doi.org/10.1088/1742-6596/1327/1/012051openalex-snapshot
Solar photovoltaic power output forecasting using machine learning technique
inferred← citeshttps://doi.org/10.1088/1755-1315/599/1/012032openalex-snapshot
Modelling of photovoltaic system power prediction based on environmental conditions using neural network single and multiple hidden layers
inferred← citeshttps://doi.org/10.1093/jigpal/jzac040openalex-snapshot
Intelligent model for active power prediction of a small wind turbine
inferred← citeshttps://doi.org/10.1109/access.2022.3156942openalex-snapshot
A Review of Machine Learning-Based Photovoltaic Output Power Forecasting: Nordic Context
inferred← citeshttps://doi.org/10.1109/access.2025.3649764openalex-snapshot
Quantifying the Economic Loss and Operational Implications of Air Pollution on Grid-Connected PV Systems in the Arabian Peninsula: A Machine Learning-Based Analysis
inferred← citeshttps://doi.org/10.1109/ai2e64943.2025.10983092openalex-snapshot
Short-Term Photovoltaic Power Forecasting-Based Kernel Ridge Regression
inferred← citeshttps://doi.org/10.1109/dese54285.2021.9719352openalex-snapshot
Reliable Photovoltaics Output Power Prediction in Qatar
inferred← citeshttps://doi.org/10.1109/eiecc60864.2023.10456727openalex-snapshot
A short-term photovoltaic power prediction model using cyclical encoding and STL decomposition based on LSTM
inferred← citeshttps://doi.org/10.1109/ever48776.2020.9243026openalex-snapshot
Combined PV Power and Load Prediction for Building-Level Energy Management Applications
inferred← citeshttps://doi.org/10.1109/icaiss58487.2023.10250567openalex-snapshot
Machine Learning based Solar PV Power Prediction
inferred← citeshttps://doi.org/10.1109/icateee68170.2025.11406309openalex-snapshot
Enhancing Weather Prediction Accuracy via PSO-Optimized SVR and Feature Correlation
inferred← citeshttps://doi.org/10.1109/icdate58146.2023.10248868openalex-snapshot
Estimation of Solar PV Plant Output using LSTM-CNN Algorithm
inferred← citeshttps://doi.org/10.1109/icecco67619.2026.11488833openalex-snapshot
Predicting Solar Power Generation Using Machine Learning
inferred← citeshttps://doi.org/10.1109/icecet52533.2021.9698546openalex-snapshot
Photovoltaic System Ensemble Prediction System
inferred← citeshttps://doi.org/10.1109/iceet53442.2021.9659661openalex-snapshot
Power Generation Voting Prediction Model of Floating Photovoltaic System
inferred← citeshttps://doi.org/10.1109/icetran66854.2025.11114148openalex-snapshot
Data-Driven Forecasting of PV Maximum Power Point Based on Environmental Parameters Using Machine Learning
inferred← citeshttps://doi.org/10.1109/iciccs51141.2021.9432322openalex-snapshot
Solar Energy Prediction using Decision Tree Regressor
inferred← citeshttps://doi.org/10.1109/icmnwc63764.2024.10872032openalex-snapshot
Enhanced Photovoltaic Power Forecasting in Renewable Energy Systems Using Genetic Algorithm and SVM Approaches
inferred← citeshttps://doi.org/10.1109/icscc62041.2024.10690608openalex-snapshot
Comparative Analysis of Machine Learning Models for Solar Power Generation Prediction
inferred← citeshttps://doi.org/10.1109/ictmim65579.2025.10988147openalex-snapshot
A Hybrid CNN-XGAOA Approach for Photovoltaic Power Output Prediction using Environmental Features
inferred← citeshttps://doi.org/10.1109/icufn61752.2024.10625232openalex-snapshot
Fusion Between Image Processing and Machine Learning for Dust Detection on Solar Panels
inferred← citeshttps://doi.org/10.1109/igarss55030.2025.11243729openalex-snapshot
Cross-City Solar Power Prediction: Feature Reduction and ML Model Comparison
inferred← citeshttps://doi.org/10.1109/irec52758.2021.9624896openalex-snapshot
Machine Learning for Solar Power Systems-A short tour
inferred← citeshttps://doi.org/10.1109/isee59483.2023.10299878openalex-snapshot
A combined neural network model for forecasting solar energy from multiple weather parameters
inferred← citeshttps://doi.org/10.1109/ispds58840.2023.10235417openalex-snapshot
BP Neural Network-Assisted Power Prediction for Photovoltaic Power Station
inferred← citeshttps://doi.org/10.1109/jphotov.2022.3226711openalex-snapshot
Experimental Studies for Glass Light Transmission Degradation in Solar Cells Due to Dust Accumulation Using Effective Optical Scattering Parameters and Machine Learning Algorithm
inferred← citeshttps://doi.org/10.1109/odicon62106.2024.10797527openalex-snapshot
Analyzing the Predictive Power of Solar Photovoltaics Using Three Machine Learning Models
inferred← citeshttps://doi.org/10.1109/piicon56320.2022.10045094openalex-snapshot
Real-Time Modelling and Controlling of Boost Converter Using Supervised Learning
inferred← citeshttps://doi.org/10.1109/saci66288.2025.11030195openalex-snapshot
Machine Learning-Based Classification for Identifying Manufacturing Parameters Influencing Current and Voltage in Dye Sensitized Sola Cells
inferred← citeshttps://doi.org/10.1109/synasc65383.2024.00061openalex-snapshot
Data-Driven Modeling of Photovoltaic Panels Using Neural Networks
inferred← citeshttps://doi.org/10.1109/wiecon-ece69386.2025.11525989openalex-snapshot
Design and Forecast Optimization of a Household Solar Pv and Energy Storage System with Machine Learning Methods
inferred← citeshttps://doi.org/10.1145/3661167.3661201openalex-snapshot
AI-enabled efficient PVM performance monitoring
inferred← citeshttps://doi.org/10.1155/2022/1541938openalex-snapshot
Prediction of Rooftop Photovoltaic Solar Potential Using Machine Learning
inferred← citeshttps://doi.org/10.1155/2022/4905980openalex-snapshot
Prediction of Photovoltaic Power by ANN Based on Various Environmental Factors in India
inferred← citeshttps://doi.org/10.1155/2022/4921153openalex-snapshot
Improving the Efficiency of Photovoltaic Panels Using Machine Learning Approach
inferred← citeshttps://doi.org/10.1155/2022/5680635openalex-snapshot
Machine Learning Based Prediction of Output PV Power in India and Malaysia with the Use of Statistical Regression
inferred← citeshttps://doi.org/10.1155/2024/1050785openalex-snapshot
Latest Advancements in Solar Photovoltaic‐Thermoelectric Conversion Technologies: Thermal Energy Storage Using Phase Change Materials, Machine Learning, and 4E Analyses
inferred← citeshttps://doi.org/10.1155/er/1140262openalex-snapshot
Forecasting the Potential, Power and Energy (PPE) of Both Building Integrated PV and Traditional PV (BIPV–PV) Systems Using State‐of‐the‐Art AI Methods
inferred← citeshttps://doi.org/10.11591/ijece.v13i3.pp2449-2458openalex-snapshot
Sensitivity of solar panel energy conversion at sunrise and sunset on three weather fluctuations in equatorial climate
inferred← citeshttps://doi.org/10.1177/09544089241255931openalex-snapshot
Synergistic approach to tribological characterization of hybrid aluminum metal matrix composites with ZrB 2 and fly ash: Experimental and predictive insights
inferred← citeshttps://doi.org/10.1186/s40807-023-00096-7openalex-snapshot
Analysis of solar energy potentials of five selected south-east cities in nigeria using deep learning algorithms
inferred← citeshttps://doi.org/10.1371/journal.pone.0324047openalex-snapshot
Predictive hybrid model of a grid-connected photovoltaic system with DC-DC converters under extreme altitude conditions at 3800 meters above sea level
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1809187/v1openalex-snapshot
Machine Learning Based PV Power Prediction Using Different Environmental Parameters of Turkey
inferred← citeshttps://doi.org/10.22399/ijcesen.1092openalex-snapshot
Designing integrated intelligent control systems for photovoltaic cooling and dust panels based on IoT: Kirkuk study, Iraq
inferred← citeshttps://doi.org/10.23889/suthesis.66094openalex-snapshot
Forecasting and Prediction of Solar Energy Generation using Machine Learning Techniques
inferred← citeshttps://doi.org/10.24018/ejai.2024.3.2.41openalex-snapshot
Illuminating the Future: Predictive Modelling of PV Output Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.28991/hef-2022-03-04-01openalex-snapshot
Tesla Stock Close Price Prediction Using KNNR, DTR, SVR, and RFR
inferred← citeshttps://doi.org/10.32604/iasc.2023.032589openalex-snapshot
Hyperparameter Optimization Based Deep Belief Network for Clean Buses Using Solar Energy Model
inferred← citeshttps://doi.org/10.3389/fenrg.2022.815256openalex-snapshot
An Integrated AMPSO-CLSTM Model for Photovoltaic Power Generation Prediction
inferred← citeshttps://doi.org/10.3389/fenrg.2023.1221006openalex-snapshot
Green hydrogen production ensemble forecasting based on hybrid dynamic optimization algorithm
inferred← citeshttps://doi.org/10.3389/fenrg.2026.1807361openalex-snapshot
Air pollution and meteorological factors significantly enhance solar radiation forecasting accuracy in the western mediterranean region: a machine learning approach
inferred← citeshttps://doi.org/10.3389/fpls.2022.1031748openalex-snapshot
Deep learning-based segmentation and classification of leaf images for detection of tomato plant disease
inferred← citeshttps://doi.org/10.3390/agriengineering3020020openalex-snapshot
Automatic and Reliable Leaf Disease Detection Using Deep Learning Techniques
inferred← citeshttps://doi.org/10.3390/app10175975openalex-snapshot
A Survey of Machine Learning Models in Renewable Energy Predictions
inferred← citeshttps://doi.org/10.3390/app12073349openalex-snapshot
Prediction Model for the Performance of Different PV Modules Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.3390/app9194034openalex-snapshot
Autonomous Installations for Monitoring the “Protector Prosperina“ Forest
inferred← citeshttps://doi.org/10.3390/buildings13082050openalex-snapshot
Enhancing Zero-Energy Building Operations for ESG: Accurate Solar Power Prediction through Automatic Machine Learning
inferred← citeshttps://doi.org/10.3390/computation11110232openalex-snapshot
Development of AI-Based Tools for Power Generation Prediction
inferred← citeshttps://doi.org/10.3390/electronics14050866openalex-snapshot
Using Machine Learning Algorithms to Forecast Solar Energy Power Output
inferred← citeshttps://doi.org/10.3390/electronics9020315openalex-snapshot
Machine Learning Based Approaches for Modeling the Output Power of Photovoltaic Array in Real Outdoor Conditions
inferred← citeshttps://doi.org/10.3390/en12183564openalex-snapshot
Evaluation of Photovoltaic Power Generation by Using Deep Learning in Solar Panels Installed in Buildings
inferred← citeshttps://doi.org/10.3390/en12224352openalex-snapshot
Genetic Algorithm Approach to Design of Multi-Layer Perceptron for Combined Cycle Power Plant Electrical Power Output Estimation
inferred← citeshttps://doi.org/10.3390/en13030735openalex-snapshot
A Machine Learning Approach to Low-Cost Photovoltaic Power Prediction Based on Publicly Available Weather Reports
inferred← citeshttps://doi.org/10.3390/en13153994openalex-snapshot
A Case Study to Identify the Hindrances to Widespread Adoption of Electric Vehicles in Qatar
inferred← citeshttps://doi.org/10.3390/en13236405openalex-snapshot
Novel Mode Adaptive Artificial Neural Network for Dynamic Learning: Application in Renewable Energy Sources Power Generation Prediction
inferred← citeshttps://doi.org/10.3390/en14217146openalex-snapshot
Comprehensive and Comparative Analysis of GAM-Based PV Power Forecasting Models Using Multidimensional Tensor Product Splines against Machine Learning Techniques
inferred← citeshttps://doi.org/10.3390/en15051836openalex-snapshot
Investigation of a Real-Time Dynamic Model for a PV Cooling System
inferred← citeshttps://doi.org/10.3390/en15072589openalex-snapshot
Power Generation Prediction of Building-Integrated Photovoltaic System with Colored Modules Using Machine Learning
inferred← citeshttps://doi.org/10.3390/en15155404openalex-snapshot
Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review
inferred← citeshttps://doi.org/10.3390/en15197222openalex-snapshot
Machine Learning Analysis on the Performance of Dye-Sensitized Solar Cell—Thermoelectric Generator Hybrid System
inferred← citeshttps://doi.org/10.3390/en15218201openalex-snapshot
Approximating Shading Ratio Using the Total-Sky Imaging System: An Application for Photovoltaic Systems
inferred← citeshttps://doi.org/10.3390/en16124696openalex-snapshot
Photovoltaic Power Forecasting Using Multiscale-Model-Based Machine Learning Techniques
inferred← citeshttps://doi.org/10.3390/en16196842openalex-snapshot
New Feature Selection Approach for Photovoltaïc Power Forecasting Using KCDE
inferred← citeshttps://doi.org/10.3390/en17102307openalex-snapshot
Optimizing Nanofluid Hybrid Solar Collectors through Artificial Intelligence Models
inferred← citeshttps://doi.org/10.3390/en17164145openalex-snapshot
Forecasting Solar Photovoltaic Power Production: A Comprehensive Review and Innovative Data-Driven Modeling Framework
inferred← citeshttps://doi.org/10.3390/en17215431openalex-snapshot
Enhancing Regional Wind Power Forecasting through Advanced Machine-Learning and Feature-Selection Techniques
inferred← citeshttps://doi.org/10.3390/en17235844openalex-snapshot
Panel Temperature Dependence on Atmospheric Parameters of an Operative Photovoltaic Park in Semi-Arid Zones Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.3390/en18061318openalex-snapshot
Machine Learning-Based Evaluation of Solar Photovoltaic Panel Exergy and Efficiency Under Real Climate Conditions
inferred← citeshttps://doi.org/10.3390/en18133458openalex-snapshot
Using Machine Learning and Analytical Modeling to Predict Poly-Crystalline PV Performance in Jordan
inferred← citeshttps://doi.org/10.3390/en18185011openalex-snapshot
Machine Learning-Based Prediction of Dye-Sensitized Solar Cell Efficiency for Manufacturing Process Optimization
inferred← citeshttps://doi.org/10.3390/forecast5010012openalex-snapshot
A Day-Ahead Photovoltaic Power Prediction via Transfer Learning and Deep Neural Networks
inferred← citeshttps://doi.org/10.3390/info14110617openalex-snapshot
Neural Network-Based Solar Irradiance Forecast for Edge Computing Devices
inferred← citeshttps://doi.org/10.3390/rs13132605openalex-snapshot
A Novel Hybrid Spatio-Temporal Forecasting of Multisite Solar Photovoltaic Generation
inferred← citeshttps://doi.org/10.3390/s20113127openalex-snapshot
Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.3390/s20195637openalex-snapshot
Design, Construction and Testing of IoT Based Automated Indoor Vertical Hydroponics Farming Test-Bed in Qatar
inferred← citeshttps://doi.org/10.3390/su12198127openalex-snapshot
Fuel Cell Characteristic Curve Approximation Using the Bézier Curve Technique
inferred← citeshttps://doi.org/10.3390/su13042393openalex-snapshot
Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.3390/su13063364openalex-snapshot
Quantification of PV Power and Economic Losses Due to Soiling in Qatar
inferred← citeshttps://doi.org/10.3390/su15097087openalex-snapshot
Forecasting Renewable Energy Generation with Machine Learning and Deep Learning: Current Advances and Future Prospects
inferred← citeshttps://doi.org/10.3390/su17010174openalex-snapshot
Performance Evaluation of Photovoltaic Panels in Extreme Environments: A Machine Learning Approach on Horseshoe Island, Antarctica
inferred← citeshttps://doi.org/10.37247/pas.1.2021.40openalex-snapshot
Quantification of PV Power and Economic Losses Due to Soiling in Qatar
inferred← citeshttps://doi.org/10.37934/arfmts.120.1.112openalex-snapshot
Application of Machine Learning to Forecast Solar Photovoltaic Output Power
inferred← citeshttps://doi.org/10.3934/geosci.2024035openalex-snapshot
AI-Driven precision in solar forecasting: Breakthroughs in machine learning and deep learning
inferred← citeshttps://doi.org/10.4018/979-8-3693-2355-7.ch004openalex-snapshot
A Study of Computer Vision, Deep Learning, and Machine Learning Techniques for Forecasting Solar Power and Renewable Energy
inferred← citeshttps://doi.org/10.4018/ijdst.307955openalex-snapshot
Designing Collaborative Edge Computing for Electricity Heterogeneous Data Based on Social IoT Systems
inferred← citeshttps://doi.org/10.48175/ijarsct-17860openalex-snapshot
IOT Based Automated Hydroponics System for Precision Agriculture
inferred← citeshttps://doi.org/10.5121/csit.2022.1220openalex-snapshot
Signal, Image Processing and Embedded Systems Trends
inferred← citeshttps://doi.org/10.5121/csit.2022.122001openalex-snapshot
Classification of Viral, Bacterial, And Covid-19 Pneumonia using Deep Learning Framework from Chest X-Ray Images
inferred← citeshttps://doi.org/10.56294/sctconf2023465openalex-snapshot
Machine Learning for predicting climate change in the environment: Review
inferred← citeshttps://doi.org/10.5772/intechopen.92632openalex-snapshot
Photo-Voltaic (PV) Monitoring System, Performance Analysis and Power Prediction Models in Doha, Qatar
inferred← citeshttps://doi.org/10.5772/intechopen.97319openalex-snapshot
Tomato Leaf Diseases Detection Using Deep Learning Technique
inferred← citeshttps://doi.org/10.61112/jiens.1620198openalex-snapshot
Estimation of power outputs of two different photovoltaic solar panels with different heuristic algorithms
inferred← citeshttps://doi.org/10.61186/crpase.9.3.2860openalex-snapshot
Review of Machine Learning Techniques for Power Electronics Control and Optimization
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.