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Application of ANN technique to predict the performance of solar collector systems - A review

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  1. Fan, Guo-Feng & Peng, Li-Ling & Hong, Wei-Chiang, 2018. "Short term load forecasting based on phase space reconstruction algorithm and bi-square kernel regression model," Applied Energy, Elsevier, vol. 224(C), pages 13-33.
  2. Mostafa Esmaeili Shayan & Gholamhassan Najafi & Barat Ghobadian & Shiva Gorjian & Mohamed Mazlan & Mehdi Samami & Alireza Shabanzadeh, 2022. "Flexible Photovoltaic System on Non-Conventional Surfaces: A Techno-Economic Analysis," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
  3. Heo, SungKu & Byun, Jaewon & Ifaei, Pouya & Ko, Jaerak & Ha, Byeongmin & Hwangbo, Soonho & Yoo, ChangKyoo, 2024. "Towards mega-scale decarbonized industrial park (Mega-DIP): Generative AI-driven techno-economic and environmental assessment of renewable and sustainable energy utilization in petrochemical industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
  4. Feng, Y.H. & Dai, Y.J. & Wang, R.Z. & Ge, T.S., 2022. "Insights into desiccant-based internally-cooled dehumidification using porous sorbents: From a modeling viewpoint," Applied Energy, Elsevier, vol. 311(C).
  5. Wang, Zhangyuan & Zhao, Xudong & Han, Zhonghe & Luo, Liang & Xiang, Jinwei & Zheng, Senglin & Liu, Guangming & Yu, Min & Cui, Yu & Shittu, Samson & Hu, Menglong, 2021. "Advanced big-data/machine-learning techniques for optimization and performance enhancement of the heat pipe technology – A review and prospective study," Applied Energy, Elsevier, vol. 294(C).
  6. Sujan Ghimire & Ravinesh C Deo & Nawin Raj & Jianchun Mi, 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction," Energies, MDPI, vol. 12(12), pages 1-39, June.
  7. Mustafa Jaihuni & Jayanta Kumar Basak & Fawad Khan & Frank Gyan Okyere & Elanchezhian Arulmozhi & Anil Bhujel & Jihoon Park & Lee Deog Hyun & Hyeon Tae Kim, 2020. "A Partially Amended Hybrid Bi-GRU—ARIMA Model (PAHM) for Predicting Solar Irradiance in Short and Very-Short Terms," Energies, MDPI, vol. 13(2), pages 1-20, January.
  8. Ajbar, Wassila & Parrales, A. & Huicochea, A. & Hernández, J.A., 2022. "Different ways to improve parabolic trough solar collectors’ performance over the last four decades and their applications: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  9. Du, Bin & Lund, Peter D. & Wang, Jun, 2021. "Combining CFD and artificial neural network techniques to predict the thermal performance of all-glass straight evacuated tube solar collector," Energy, Elsevier, vol. 220(C).
  10. Zhang, Yuanting & Li, Qing & Qiu, Yu, 2024. "Real-time and annual performance evaluation of an ultra-high-temperature concentrating solar collector by developing an MCRT-CFD-ANN coupled model," Energy, Elsevier, vol. 307(C).
  11. Mousavi, Rashin & Mousavi, Arash & Mousavi, Yashar & Tavasoli, Mahsa & Arab, Aliasghar & Kucukdemiral, Ibrahim Beklan & Alfi, Alireza & Fekih, Afef, 2025. "Revolutionizing solar energy resources: The central role of generative AI in elevating system sustainability and efficiency," Applied Energy, Elsevier, vol. 382(C).
  12. Dimri, Neha & Tiwari, Arvind & Tiwari, G.N., 2019. "Comparative study of photovoltaic thermal (PVT) integrated thermoelectric cooler (TEC) fluid collectors," Renewable Energy, Elsevier, vol. 134(C), pages 343-356.
  13. Rana, Mashud & Sethuvenkatraman, Subbu & Heidari, Rahmat & Hands, Stuart, 2022. "Solar thermal generation forecast via deep learning and application to buildings cooling system control," Renewable Energy, Elsevier, vol. 196(C), pages 694-706.
  14. Harish Kumar Ghritlahre & Purvi Chandrakar & Ashfaque Ahmad, 2021. "A Comprehensive Review on Performance Prediction of Solar Air Heaters Using Artificial Neural Network," Annals of Data Science, Springer, vol. 8(3), pages 405-449, September.
  15. Unterberger, Viktor & Lichtenegger, Klaus & Kaisermayer, Valentin & Gölles, Markus & Horn, Martin, 2021. "An adaptive short-term forecasting method for the energy yield of flat-plate solar collector systems," Applied Energy, Elsevier, vol. 293(C).
  16. Ibrahim Sufian Osman & Nasir Ghazi Hariri, 2022. "Thermal Investigation and Optimized Design of a Novel Solar Self-Driven Thermomechanical Actuator," Sustainability, MDPI, vol. 14(9), pages 1-23, April.
  17. Vakili, Masoud & Yahyaei, Masood & Ramsay, James & Aghajannezhad, Pouria & Paknezhad, Behnaz, 2021. "Adaptive neuro-fuzzy inference system modeling to predict the performance of graphene nanoplatelets nanofluid-based direct absorption solar collector based on experimental study," Renewable Energy, Elsevier, vol. 163(C), pages 807-824.
  18. Zafer Utlu & Mert Tolon & Arif Karabuga, 2021. "Modelling of energy and exergy analysis of ORC integrated systems in terms of sustainability by applying artificial neural network [Thermodynamic performance evaluation of a novel solar energy base," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 16(1), pages 156-164.
  19. Li, B. & Delpha, C. & Diallo, D. & Migan-Dubois, A., 2021. "Application of Artificial Neural Networks to photovoltaic fault detection and diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
  20. L, Chilambarasan & Thangarasu, Vinoth & Ramasamy, Prakash, 2024. "Solar flat plate collector's heat transfer enhancement using grooved tube configuration with alumina nanofluids: Prediction of outcomes through artificial neural network modeling," Energy, Elsevier, vol. 289(C).
  21. Zixia Yuan & Guojiang Xiong & Xiaofan Fu, 2022. "Artificial Neural Network for Fault Diagnosis of Solar Photovoltaic Systems: A Survey," Energies, MDPI, vol. 15(22), pages 1-18, November.
  22. Zendehboudi, Sohrab & Rezaei, Nima & Lohi, Ali, 2018. "Applications of hybrid models in chemical, petroleum, and energy systems: A systematic review," Applied Energy, Elsevier, vol. 228(C), pages 2539-2566.
  23. Yesilyurt, Hasan & Dokuz, Yesim & Dokuz, Ahmet Sakir, 2024. "Data-driven energy consumption prediction of a university office building using machine learning algorithms," Energy, Elsevier, vol. 310(C).
  24. Visarion Cătălin Ifrim & Laurențiu Dan Milici & Pavel Atănăsoae & Daniela Irimia & Radu Dumitru Pentiuc, 2022. "Future Research Tendencies and Possibilities of Using Cogeneration Applications of Solar Air Heaters: A Bibliometric Analysis," Energies, MDPI, vol. 15(19), pages 1-24, September.
  25. Shayan, Mostafa Esmaeili & Najafi, Gholamhassan & Ghobadian, Barat & Gorjian, Shiva & Mamat, Rizalman & Ghazali, Mohd Fairusham, 2022. "Multi-microgrid optimization and energy management under boost voltage converter with Markov prediction chain and dynamic decision algorithm," Renewable Energy, Elsevier, vol. 201(P2), pages 179-189.
  26. Gkousis, Spiros & Braimakis, Konstantinos & Nimmegeers, Philippe & Karellas, Sotirios & Compernolle, Tine, 2025. "Multi-objective optimization of medium-enthalpy geothermal Organic Rankine Cycle plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 210(C).
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