Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Xiaorui Shao"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The job shop scheduling problem (JSSP) is critical for building one smart factory regarding resource management, effective production, and intelligent supply. However, it is still very challenging due to the complex production environment. B
Externí odkaz:
https://doaj.org/article/5ff6953306ae4ceebd6c6a91244f3e50
Autor:
Xiaorui Shao, Chang Soo Kim
Publikováno v:
IEEE Access, Vol 10, Pp 88079-88092 (2022)
This manuscript proposed an effective hybrid method based on multi-level convolutional neural network (ML-CNN) and iterative local search (ILS) to solve job shop scheduling problems (JSSP) with small scale training samples and less time. In the propo
Externí odkaz:
https://doaj.org/article/93a44596d0ea4467bb2090f80fb2c3ff
Publikováno v:
IEEE Access, Vol 9, Pp 157447-157457 (2021)
Accurate gas consumption and elapsed time forecasting can help decision-makers detect anomaly gas usage and notify users to recognize the facility fault in real-time. However, it is challenging due to its variable and complex factors. This paper prop
Externí odkaz:
https://doaj.org/article/2245f4490d44432493268d92ba287031
Autor:
Xiaorui Shao, Chang Soo Kim
Publikováno v:
IEEE Access, Vol 8, Pp 125263-125273 (2020)
Short-Term Load Forecasting (STLF) is one critical assignment regarding the power supply and demand in the smart grid. Multi-step STLF provides strong evidence for decision-making to achieve consistent, quick supply and reduce direct or indirect cost
Externí odkaz:
https://doaj.org/article/8c54eef622e44e629a9a1d31429d4b75
Publikováno v:
IEEE Access, Vol 8, Pp 188352-188362 (2020)
Short-term power consumption forecasting plays a critical role in the process of building the smart grid. However, it is very challenging as the power consumption series has strong randomness and volatility. In this paper, the authors proposed a nove
Externí odkaz:
https://doaj.org/article/61ebc75eb18743aa8b4b474608355e68
Autor:
Xiaorui Shao, Chang-Soo Kim
Publikováno v:
Sensors, Vol 22, Iss 11, p 4156 (2022)
Fault diagnosis (FD) plays a vital role in building a smart factory regarding system reliability improvement and cost reduction. Recent deep learning-based methods have been applied for FD and have obtained excellent performance. However, most of the
Externí odkaz:
https://doaj.org/article/c5917216b8e44cb4af525b700c07b517
Publikováno v:
Energies, Vol 13, Iss 8, p 1881 (2020)
Electricity consumption forecasting is a vital task for smart grid building regarding the supply and demand of electric power. Many pieces of research focused on the factors of weather, holidays, and temperatures for electricity forecasting that requ
Externí odkaz:
https://doaj.org/article/aad3ab8aa2a048f3bac2b2230705e297
Publikováno v:
KSII Transactions on Internet & Information Systems; Apr2024, Vol. 18 Issue 4, p843-859, 17p
Publikováno v:
Neurocomputing. 501:258-269
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4392094ccc4c0696068eeb2dfbef0c60
https://doi.org/10.1016/j.neucom.2022.06.026
https://doi.org/10.1016/j.neucom.2022.06.026
Autor:
Chang Soo Kim, Xiaorui Shao
Publikováno v:
Computers, Materials & Continua. 70:5143-5160
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::75540dad79d99ad70de5ba70d1466a57
https://doi.org/10.32604/cmc.2022.020689
https://doi.org/10.32604/cmc.2022.020689