Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jieyang Peng"'
Autor:
Jieyang, Peng1,2 (AUTHOR), Kimmig, Andreas2 (AUTHOR), Dongkun, Wang3 (AUTHOR), Niu, Zhibin4 (AUTHOR) zniu@tju.edu.cn, Zhi, Fan5 (AUTHOR), Jiahai, Wang1 (AUTHOR), Liu, Xiufeng6 (AUTHOR), Ovtcharova, Jivka2 (AUTHOR)
Publikováno v:
Journal of Intelligent Manufacturing. Dec2023, Vol. 34 Issue 8, p3277-3304. 28p.
Akademický článek
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Publikováno v:
New Digital Work ISBN: 9783031264894
The way humans work is constantly changing. This has always been the case, especially in dynamic environments. In the context of Industry 4.0 and the Internet of Things (IoT), collaborative platforms, accelerated by Artificial Intelligence (AI) techn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c7806432329c46e628bc6ad2ddc6659
https://doi.org/10.1007/978-3-031-26490-0_15
https://doi.org/10.1007/978-3-031-26490-0_15
Publikováno v:
2021 XXX International Scientific Conference Electronics (ET).
CNC machine tools play a pivotal role in the manufacturing field. Due to the complexity and diversity of faults, experienced engineers who can quickly locate the cause of faults are rather scarce. This paper takes expert knowledge in the field of fau
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a893bdfdf5e75a7d7f92770a9c30018a
https://doi.org/10.1109/et52713.2021.9579568
https://doi.org/10.1109/et52713.2021.9579568
Publikováno v:
Energy and buildings, 249, Art.-Nr.: 111211
Energy and Buildings
Peng, J, Kimmig, A, Wang, J, Liu, X, Niu, Z & Ovtcharova, J 2021, ' Dual-stage attention-based long-short-term memory neural networks for energy demand prediction ', Energy and Buildings, vol. 249, 111211 . https://doi.org/10.1016/j.enbuild.2021.111211
Energy and Buildings
Peng, J, Kimmig, A, Wang, J, Liu, X, Niu, Z & Ovtcharova, J 2021, ' Dual-stage attention-based long-short-term memory neural networks for energy demand prediction ', Energy and Buildings, vol. 249, 111211 . https://doi.org/10.1016/j.enbuild.2021.111211
Forecasting energy demand of residential buildings plays an important role in the operation of smart cities, as it forms the basis for decision-making in the planning and operation of urban energy systems. Deep learning algorithms are commonly used t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcf25850715a2d96c3a3bfa4fc04330c
https://publikationen.bibliothek.kit.edu/1000138050
https://publikationen.bibliothek.kit.edu/1000138050
An Advanced IoT Platform and its Implementations Focused on Modern Information Technology Generation
Autor:
Jivka Ovtcharova, Grethler Michael, Andreas Kimmig, Jiahai Wang, Marin B. Marinov, Jieyang Peng
Publikováno v:
2020 XI National Conference with International Participation (ELECTRONICA).
With the introduction of a new wave of IT in production and the deep convergence between information technology and industry, industrial production is developing towards intellectualization and networking. Because the current production system cannot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7d0dade1754d4cdc9a909ee9f56be362
https://doi.org/10.1109/electronica50406.2020.9305135
https://doi.org/10.1109/electronica50406.2020.9305135
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030539559
ICSI
ICSI
The Job Shop Scheduling problem is critical in the manufacturing industry. At present, the decision tree reasoning technique and data mining are often used in multi-objective optimization research to solve flexible job shop scheduling issues. Unfortu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::09909f4f2d84a64d44e548116afb311f
https://doi.org/10.1007/978-3-030-53956-6_10
https://doi.org/10.1007/978-3-030-53956-6_10
Publikováno v:
Peng, J, Kimmig, A, Niu, Z, Wang, J, Liu, X & Ovtcharova, J 2021, ' A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework ', Applied Energy, vol. 299, 117321 . https://doi.org/10.1016/j.apenergy.2021.117321
Understanding urban demand profiles is an important determinant for energy dispatch and the optimization of the electric energy supply. For the design of the energy supply system, an important consideration is, to express the characteristics of urban
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a9608903a4f785c93f805626750e9152
https://doi.org/10.1016/j.apenergy.2021.117321
https://doi.org/10.1016/j.apenergy.2021.117321
Autor:
Jieyang, Peng, Dongkun, Wang, Kimmig, Andreas, Langovoy, Mikhail A., Jiahai, Wang, Ovtcharova, Jivka
Publikováno v:
Automatisierungstechnik; Jan2021, Vol. 69 Issue 1, p73-83, 11p