Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Siteng Wang"'
Publikováno v:
IEEE Access, Vol 12, Pp 98647-98659 (2024)
Accurate power load forecasting for large industrial users plays a crucial role in developing effective power consumption plans and energy-saving strategies. It also contributes to optimizing the operational efficiency of the power grid. To enhance t
Externí odkaz:
https://doaj.org/article/f8ddb66b9eae458f918e3750987aa75b
Publikováno v:
Energy Reports, Vol 9, Iss , Pp 238-246 (2023)
A short-term power load forecasting (STPLF) model based on the Improved Whale Optimization Algorithm (IWOA) optimized Kernel Extreme Learning Machine (KELM) is proposed to address the problems of high randomness and low forecasting accuracy of electr
Externí odkaz:
https://doaj.org/article/2f614087091a4489b74d3ed1404fc0d1
Autor:
Shidan, Zhang, Song, Liang, Yumin, Zhang, Rong, Chen, Siteng, Wang, Meirong, Li, Guangjin, Liu
Publikováno v:
In Microbial Pathogenesis October 2024 195
Publikováno v:
The 4th International Conference on Information Technologies and Electrical Engineering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b169703552b3e5588dd686fbb59275dd
https://doi.org/10.1145/3513142.3513208
https://doi.org/10.1145/3513142.3513208
Autor:
Yue Su, Hongping Deng, Ping Huang, Deyue Yan, Xinyuan Zhu, Xiaohua Huang, Pei Sun, Jian Shen, Siteng Wang
Publikováno v:
RSC Advances. 6:12472-12478
A new self-tracking nanoscale drug delivery system has been developed to monitor drug delivery and release in tumor cells. The small molecule nanodrug was constructed via the conjugation and self-assembly of two widely used anticancer drugs, hydrophi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a65d620a639e28e989afdc9229a0c6b3
https://doi.org/10.1039/c5ra24273h
https://doi.org/10.1039/c5ra24273h
Autor:
Siteng Wang, Huawei Zhang
Publikováno v:
2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC).
The data shows that about 20% of car failures come from the rear axle of the car. Accordingly we use a support vector machine based on optimization algorithm of Drosophila melanogaster as the fault diagnosis method. The vibration signal is denoised b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a33861bfcfc3fd162e5f207d8f8f5c93
https://doi.org/10.1109/iaeac.2017.8054467
https://doi.org/10.1109/iaeac.2017.8054467