Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks

Xiaobin HU, (Yanshan University, Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Qinhuangdao, China)
Peifeng NIU, (Yanshan University, Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Qinhuangdao, China)
Jianmei WANG, (Hebei Normal University of Science and Technology, College of Horticulture Science and Technology, Qinhuangdao, China)
Xinxin ZHANG (Yanshan University, Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment, Qinhuangdao, China)
Atmospheric Pollution Research
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Yıl: 2020 Cilt: 11 Sayı: 7 Sayfa Aralığı: 1084 - 1090 Metin Dili: İngilizce DOI: 10.1016/j.apr.2020.04.001 İndeks Tarihi: 06-11-2020

Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks

Öz:
Our works frequently examine the emission of pollutants and the prediction of the thermal efficiency of boilersfrom power plants. Power plant systems are strongly coupled. Thus, multi-objective modelling and prediction isalways a difficult problem. Artificial neural network (ANN) modelling is one of the methods used to meet thischallenge. With the increasing requirements of environmental protection, the classical shallow neural networkcan no longer meet the needs of high precision. In recent years, deep neural networks have gradually demonstrated their powerful capabilities. However, can deep neural networks be used to improve model predictionperformance? After many experiments, we successfully construct a sophisticated and stable deep hybrid neuralnetwork model to achieve this requirement. The experimental results show that the performance of the hybridmodel is superior to that of the classical model; we diagram the detailed structure of the model and provide thecorresponding parameter settings in this paper.
Anahtar Kelime:

Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Bibliyografik
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APA HU X, NIU P, WANG J, ZHANG X (2020). Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. , 1084 - 1090. 10.1016/j.apr.2020.04.001
Chicago HU Xiaobin,NIU Peifeng,WANG Jianmei,ZHANG Xinxin Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. (2020): 1084 - 1090. 10.1016/j.apr.2020.04.001
MLA HU Xiaobin,NIU Peifeng,WANG Jianmei,ZHANG Xinxin Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. , 2020, ss.1084 - 1090. 10.1016/j.apr.2020.04.001
AMA HU X,NIU P,WANG J,ZHANG X Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. . 2020; 1084 - 1090. 10.1016/j.apr.2020.04.001
Vancouver HU X,NIU P,WANG J,ZHANG X Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. . 2020; 1084 - 1090. 10.1016/j.apr.2020.04.001
IEEE HU X,NIU P,WANG J,ZHANG X "Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks." , ss.1084 - 1090, 2020. 10.1016/j.apr.2020.04.001
ISNAD HU, Xiaobin vd. "Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks". (2020), 1084-1090. https://doi.org/10.1016/j.apr.2020.04.001
APA HU X, NIU P, WANG J, ZHANG X (2020). Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. Atmospheric Pollution Research, 11(7), 1084 - 1090. 10.1016/j.apr.2020.04.001
Chicago HU Xiaobin,NIU Peifeng,WANG Jianmei,ZHANG Xinxin Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. Atmospheric Pollution Research 11, no.7 (2020): 1084 - 1090. 10.1016/j.apr.2020.04.001
MLA HU Xiaobin,NIU Peifeng,WANG Jianmei,ZHANG Xinxin Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. Atmospheric Pollution Research, vol.11, no.7, 2020, ss.1084 - 1090. 10.1016/j.apr.2020.04.001
AMA HU X,NIU P,WANG J,ZHANG X Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. Atmospheric Pollution Research. 2020; 11(7): 1084 - 1090. 10.1016/j.apr.2020.04.001
Vancouver HU X,NIU P,WANG J,ZHANG X Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks. Atmospheric Pollution Research. 2020; 11(7): 1084 - 1090. 10.1016/j.apr.2020.04.001
IEEE HU X,NIU P,WANG J,ZHANG X "Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks." Atmospheric Pollution Research, 11, ss.1084 - 1090, 2020. 10.1016/j.apr.2020.04.001
ISNAD HU, Xiaobin vd. "Multi-objective prediction of coal-fired boiler with a deep hybrid neural networks". Atmospheric Pollution Research 11/7 (2020), 1084-1090. https://doi.org/10.1016/j.apr.2020.04.001
Sayfa Oluşturulma Tarihi
23-04-2024 14:51

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