Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Caiyang Yu"'
Autor:
Chenwei Tang, Caiyang Yu, Yi Gao, Jianming Chen, Jiaming Yang, Jiuling Lang, Chuan Liu, Ling Zhong, Zhenan He, Jiancheng Lv
Publikováno v:
Big Data Mining and Analytics, Vol 5, Iss 2, Pp 140-160 (2022)
As a high-tech strategic emerging comprehensive industry, the nuclear industry is committed to the research, production, and processing of nuclear fuel, as well as the development and utilization of nuclear energy. Nowadays, the nuclear industry has
Externí odkaz:
https://doaj.org/article/93e933753aeb445fa28e33c5a2e709dd
Publikováno v:
Energies, Vol 16, Iss 15, p 5644 (2023)
The optimal configuration of the rated capacity, rated power and daily output power is an important prerequisite for energy storage systems to participate in peak regulation on the grid side. Economic benefits are the main reason driving investment i
Externí odkaz:
https://doaj.org/article/21ac0bd0e904411c9e4ec2419bee79ed
Publikováno v:
Sustainability; Volume 15; Issue 11; Pages: 8634
To solve the voltage stability problem of electric vehicles connected to the distribution network in the limit state, a reactive power compensation strategy based on the holomorphic embedding method and electrical distance is proposed. Firstly, the l
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90735e6a5863725b4a35ba7a79046844
Publikováno v:
Engineering with Computers. 38:3761-3788
An improved grasshopper optimization algorithm (GOA) is proposed in this paper, termed as SGOA, which combines simulated annealing (SA) mechanism with the original GOA that is a natural optimizer widely used in finance, medical and other fields, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::86ae1c571531274a9a31167e16a88203
https://doi.org/10.1007/s00366-020-01234-1
https://doi.org/10.1007/s00366-020-01234-1
Autor:
Xuehua Zhao, Zhennao Cai, Chengye Li, Guoxi Liang, Xiaojia Ye, Caiyang Yu, Huiling Chen, Mingjing Wang
Publikováno v:
Mathematics and Computers in Simulation. 178:259-289
This study proposed an improved dragonfly algorithm (DA). This algorithm is a recently proposed metaheuristic optimizer inspired by swarming behaviors of dragonflies, which has reasonably achieved satisfactory results in dealing with engineering, edu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5e614649ea807ecd253f8dc55d36e8b7
https://doi.org/10.1016/j.matcom.2020.06.012
https://doi.org/10.1016/j.matcom.2020.06.012
Publikováno v:
Applied Mathematical Modelling. 87:1-19
This study develops an improved moth-flame optimization algorithm, which is a recently proposed optimizer based on moth behavior in nature. It has achieved favorable results in medical science, educational evaluation, and other fields. However, the c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::859193ec82c2ba2568b77b67fe947af6
https://doi.org/10.1016/j.apm.2020.04.019
https://doi.org/10.1016/j.apm.2020.04.019
Publikováno v:
Expert Systems with Applications. 181:115082
The slime mould algorithm is an interesting swarm-based algorithm proposed in 2020 based on this entity's trajectory finding abilities in nature. It simulates slime mould movement, foraging, and other behaviors to find the problem's optimal solution.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9e113df48a6171a14004b5e243baa93
https://doi.org/10.1016/j.eswa.2021.115082
https://doi.org/10.1016/j.eswa.2021.115082
Publikováno v:
Expert Systems with Applications. 141:112976
To cope with the potential shortcomings of classical fruit fly optimization algorithm (FOA), a new version of FOA with Gaussian mutation operator and the chaotic local search strategy (MCFOA) is proposed in this research. First, the Gaussian mutation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2716d2308f0d318cc0d10968de865daf
https://doi.org/10.1016/j.eswa.2019.112976
https://doi.org/10.1016/j.eswa.2019.112976
Autor:
Awadallah, Mohammed A.1,2 (AUTHOR) ma.awadallah@alaqsa.edu.ps, Braik, Malik Shehadeh3 (AUTHOR), Al-Betar, Mohammed Azmi4,5 (AUTHOR), Abu Doush, Iyad6,7 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Sep2023, Vol. 35 Issue 27, p20013-20068. 56p.
Autor:
Guo, Feng1 (AUTHOR) gfzjsgcc@163.com, Li, Jian1 (AUTHOR) 13857682918@163.com, Zhang, Chi1 (AUTHOR) charlyyyy2008@gmail.com, Zhu, Yizhi1 (AUTHOR) ycy_xo@163.com, Yu, Caiyang1 (AUTHOR) zyzliz@163.com, Wang, Qingsong2 (AUTHOR) qswang@seu.edu.cn, Buja, Giuseppe3 (AUTHOR) giuseppe.buja@unipd.it
Publikováno v:
Energies (19961073). Aug2023, Vol. 16 Issue 15, p5644. 13p.