Artificial neural network analysis of liquid desiccant dehumidification system
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DOI: 10.1016/j.energy.2010.11.030
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References listed on IDEAS
- Kabeel, A.E., 2010. "Dehumidification and humidification process of desiccant solution by air injection," Energy, Elsevier, vol. 35(12), pages 5192-5201.
- Zhang, L.Z., 2006. "Energy performance of independent air dehumidification systems with energy recovery measures," Energy, Elsevier, vol. 31(8), pages 1228-1242.
- Mohandes, M. & Rehman, S. & Halawani, T.O., 1998. "Estimation of global solar radiation using artificial neural networks," Renewable Energy, Elsevier, vol. 14(1), pages 179-184.
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- Rashidi, M.M. & Galanis, N. & Nazari, F. & Basiri Parsa, A. & Shamekhi, L., 2011. "Parametric analysis and optimization of regenerative Clausius and organic Rankine cycles with two feedwater heaters using artificial bees colony and artificial neural network," Energy, Elsevier, vol. 36(9), pages 5728-5740.
- Elsarrag, Esam & Igobo, Opubo N. & Alhorr, Yousef & Davies, Philip A., 2016. "Solar pond powered liquid desiccant evaporative cooling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 124-140.
- Luo, Yimo & Wang, Meng & Yang, Hongxing & Lu, Lin & Peng, Jinqing, 2015. "Experimental study of the film thickness in the dehumidifier of a liquid desiccant air conditioning system," Energy, Elsevier, vol. 84(C), pages 239-246.
- Mousapour, Ashkan & Hajipour, Alireza & Rashidi, Mohammad Mehdi & Freidoonimehr, Navid, 2016. "Performance evaluation of an irreversible Miller cycle comparing FTT (finite-time thermodynamics) analysis and ANN (artificial neural network) prediction," Energy, Elsevier, vol. 94(C), pages 100-109.
- Wang, Xinli & Cai, Wenjian & Lu, Jiangang & Sun, Youxian & Zhao, Lei, 2015. "Model-based optimization strategy of chiller driven liquid desiccant dehumidifier with genetic algorithm," Energy, Elsevier, vol. 82(C), pages 939-948.
- Bergero, Stefano & Chiari, Anna, 2011. "On the performances of a hybrid air-conditioning system in different climatic conditions," Energy, Elsevier, vol. 36(8), pages 5261-5273.
- Rashidi, M.M. & Ali, M. & Freidoonimehr, N. & Nazari, F., 2013. "Parametric analysis and optimization of entropy generation in unsteady MHD flow over a stretching rotating disk using artificial neural network and particle swarm optimization algorithm," Energy, Elsevier, vol. 55(C), pages 497-510.
- Jani, D.B. & Mishra, Manish & Sahoo, P.K., 2017. "Application of artificial neural network for predicting performance of solid desiccant cooling systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 352-366.
- Ali, Ameer & Ishaque, Kashif & Lashin, Aref & Al Arifi, Nassir, 2017. "Modeling of a liquid desiccant dehumidification system for close type greenhouse cultivation," Energy, Elsevier, vol. 118(C), pages 578-589.
- Daghigh, Roonak & Arshad, Siamand Azizi & Ensafjoee, Koosha & Hajialigol, Najmeh, 2024. "A data-driven model for a liquid desiccant regenerator equipped with an evacuated tube solar collector: Random forest regression, support vector regression and artificial neural network," Energy, Elsevier, vol. 295(C).
- Ali Pakari & Saud Ghani, 2022. "Regression Models for Performance Prediction of Internally-Cooled Liquid Desiccant Dehumidifiers," Energies, MDPI, vol. 15(5), pages 1-19, February.
- Zendehboudi, Alireza & Tatar, Afshin & Li, Xianting, 2017. "A comparative study and prediction of the liquid desiccant dehumidifiers using intelligent models," Renewable Energy, Elsevier, vol. 114(PB), pages 1023-1035.
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Keywords
Artificial neural network; Liquid desiccant; Dehumidification system; Performance analysis;All these keywords.
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