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Drying Technology
An International Journal
Volume 35, 2017 - Issue 14
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Original Articles

Desiccant wheel system modeling improvement using multiple population genetic algorithm training of neural network

Yongli YangDepartment of Mechanical Engineering, Academy of Armored Forces Engineering, Beijing, ChinaCorrespondence[email protected]
,
Hua CongDepartment of Mechanical Engineering, Academy of Armored Forces Engineering, Beijing, China
,
Pengcheng JiangDepartment of Mechanical Engineering, Academy of Armored Forces Engineering, Beijing, China
,
Fuzhou FengDepartment of Mechanical Engineering, Academy of Armored Forces Engineering, Beijing, China
,
Ping ZhangTaiyuan Satellite Launching Center, Taiyuan, China
,
Yaokai LiTaiyuan Satellite Launching Center, Taiyuan, China
&
Jinfeng HaoTaiyuan Satellite Launching Center, Taiyuan, China
 show all
Pages 1663-1674 | Published online: 09 Oct 2017

Citations (8)

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Read on this site (2)

Suhuan Bi, Bin Zhang, Liangliang Mu, Xiangqian Ding & Jing Wang. (2020) Optimization of tobacco drying process control based on reinforcement learning. Drying Technology 38:10, pages 1291-1299.
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Alex Martynenko & N. N. Misra. (2020) Machine learning in drying. Drying Technology 38:5-6, pages 596-609.
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Articles from other publishers (6)

Yurong Xi, Song Cheng, Zhenkun Gao & Meibao Yao. (2022) Modeling of tobacco loosening and conditioning system using LSTM recurrent neural networks. Modeling of tobacco loosening and conditioning system using LSTM recurrent neural networks.
Ahmed Bouchaala, Ossama Merroun & Anas Sakim. (2022) A MOPSO algorithm based on pareto dominance concept for comprehensive analysis of a conventional adsorption desiccant cooling system. Journal of Building Engineering 60, pages 105189.
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Yunus Emre Güzelel, Umutcan Olmuş, Kamil Neyfel Çerçi & Orhan Büyükalaca. (2022) New multiple regression and machine learning models of rotary desiccant wheel for unbalanced flow conditions. International Communications in Heat and Mass Transfer 134, pages 106006.
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Haiyan Wu, Zhong Ji & Mengze Li. (2019) Non-Invasive Continuous Blood-Pressure Monitoring Models Based on Photoplethysmography and Electrocardiography. Sensors 19:24, pages 5543.
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F. Comino, D. Guijo-Rubio, M. Ruiz de Adana & C. Hervás-Martínez. (2019) Validation of multitask artificial neural networks to model desiccant wheels activated at low temperature. International Journal of Refrigeration 100, pages 434-442.
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Qingrui Shi, Tingting Guo, Tingjia Yin, Zhiqiang Wang, Caihong Li, Xia Sun, Yemin Guo & Wenhao Yuan. (2018) Classification of Pericarpium Citri Reticulatae of Different Ages by Using a Voltammetric Electronic Tongue System. International Journal of Electrochemical Science 13:12, pages 11359-11374.
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