Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Huaiping Jin"'
Publikováno v:
Energies, Vol 17, Iss 18, p 4739 (2024)
Photovoltaic (PV) power generation is highly stochastic and intermittent, which poses a challenge to the planning and operation of existing power systems. To enhance the accuracy of PV power prediction and ensure the safe operation of the power syste
Externí odkaz:
https://doaj.org/article/a76b9a3884bc4ff4838aaa9479306b6c
Publikováno v:
Complexity, Vol 2022 (2022)
This paper considers two kinds of stochastic reentrant job shop scheduling problems (SRJSSP), i.e., the SRJSSP with the maximum tardiness criterion and the SRJSSP with the makespan criterion. Owing to the NP-complete complexity of the considered RJSS
Externí odkaz:
https://doaj.org/article/fdc1773c57614cab972a49f66d3b52bd
Publikováno v:
Sensors, Vol 23, Iss 3, p 1520 (2023)
In the era of big data, industrial process data are often generated rapidly in the form of streams. Thus, how to process such sequential and high-speed stream data in real time and provide critical quality variable predictions has become a critical i
Externí odkaz:
https://doaj.org/article/7a3c6c061db44e8cb850c5e42d67454e
Publikováno v:
Polymers, Vol 14, Iss 5, p 1018 (2022)
Soft sensor technology has become an effective tool to enable real-time estimations of key quality variables in industrial rubber-mixing processes, which facilitates efficient monitoring and a control of rubber manufacturing. However, it remains a ch
Externí odkaz:
https://doaj.org/article/6e88637a7c424344acce54abeabb25c7
Publikováno v:
Advances in Polymer Technology, Vol 2020 (2020)
The lack of online sensors for Mooney viscosity measurement has posed significant challenges for enabling efficient monitoring, control, and optimization of industrial rubber mixing process. To obtain real-time and accurate estimations of Mooney visc
Externí odkaz:
https://doaj.org/article/6f01dafdb3a44f75ad12d28c5d1f35ef
Publikováno v:
Sensors, Vol 21, Iss 24, p 8471 (2021)
Nowadays, soft sensor techniques have become promising solutions for enabling real-time estimation of difficult-to-measure quality variables in industrial processes. However, labeled data are often scarce in many real-world applications, which poses
Externí odkaz:
https://doaj.org/article/90accf73ff434c438a49f5567cc32e5d
Publikováno v:
Chemical Engineering Research and Design. 179:510-526
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efbe82ed9c449dec1601b829fa1696ae
https://doi.org/10.1016/j.cherd.2022.01.026
https://doi.org/10.1016/j.cherd.2022.01.026
Publikováno v:
Measurement. 217:113036
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::398e60606f1e568b487a8498173cb3b8
https://doi.org/10.1016/j.measurement.2023.113036
https://doi.org/10.1016/j.measurement.2023.113036
Publikováno v:
Renewable Energy. 174:1-18
Ensemble learning models have been widely used for wind power forecasting to facilitate efficient dispatching of power systems. However, traditional ensemble methods cannot always function well due to insufficient accuracy and diversity of base learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d17aa922f72a4e2119c9084b10d7af3
https://doi.org/10.1016/j.renene.2021.04.028
https://doi.org/10.1016/j.renene.2021.04.028
Publikováno v:
2022 IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aba5884ea8b1140a52d7e0ed368c6d9c
https://doi.org/10.1109/ddcls55054.2022.9858579
https://doi.org/10.1109/ddcls55054.2022.9858579