Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Huangke Chen"'
Publikováno v:
IEEE Access, Vol 8, Pp 40828-40837 (2020)
High energy consumption in cloud data centers has become one of the main obstacles to green cities, and an urgent problem to be solved. So far, a large number of scheduling algorithms have been developed to reduce energy consumption for executing wor
Externí odkaz:
https://doaj.org/article/961cdb40e8e34deaadafc4abbd0ced1d
Publikováno v:
IEEE Access, Vol 6, Pp 38179-38185 (2018)
Recovery of the support of a block K-sparse signal x from a linear model y = Ax + v, where A is a sensing matrix and v is a noise vector, arises from many applications. The block orthogonal matching pursuit (BOMP) algorithm is a popular block sparse
Externí odkaz:
https://doaj.org/article/9dc051f2013d4559808833c66d236400
Publikováno v:
IEEE Access, Vol 6, Pp 41314-41324 (2018)
The economic dispatch problem is a kind of challenging non-convex problem, which minimizes the total operating cost while being subject to a collection of complex equality and inequality constraints. This paper presents a novel meta-heuristic named a
Externí odkaz:
https://doaj.org/article/b98616cd5ead4b14be12321f38eb3922
Publikováno v:
Information Sciences. 623:748-766
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fd80b35767eb58cdd29947507169670
https://doi.org/10.1016/j.ins.2022.12.020
https://doi.org/10.1016/j.ins.2022.12.020
Autor:
Guohua Wu, Witold Pedrycz, Jianghan Zhu, Ponnuthurai Nagaratnam Suganthan, Huangke Chen, Wenbo Qiu
Publikováno v:
IEEE Transactions on Systems, Man, and Cybernetics: Systems. 52:1716-1730
Sorting solutions play a key role in using evolutionary algorithms (EAs) to solve many-objective optimization problems (MaOPs). Generally, different solution-sorting methods possess different advantages in dealing with distinct MaOPs. Focusing on thi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3e7f34e160890eec3feabe4ae09462a
https://doi.org/10.1109/tsmc.2020.3034180
https://doi.org/10.1109/tsmc.2020.3034180
Publikováno v:
IEEE Transactions on Services Computing. 14:1167-1178
Scheduling workflows in cloud service environment has attracted great enthusiasm, and various approaches have been reported up to now. However, these approaches often ignored the uncertainties in the scheduling environment, such as the uncertain task
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e3c6f0526f9d19b69c41ea19891dc9f8
https://doi.org/10.1109/tsc.2018.2866421
https://doi.org/10.1109/tsc.2018.2866421
Publikováno v:
IEEE Internet of Things Journal. 8:10264-10279
It is well known that deep learning is one of the most important methods for data mining. With the development of the fifth-generation mobile networks (5G) and the Internet of Things (IoT), the large volume of data collected in IoTs provides a new wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c307d6eba1c9cb3d76be0fcbe96c5c9
https://doi.org/10.1109/jiot.2020.3030783
https://doi.org/10.1109/jiot.2020.3030783
Publikováno v:
Information Sciences. 540:242-262
Emerging issues such as privacy protection and communication limitations make it not possible to collect all data into data centers, which has driven the paradigm of big data and artificial intelligence to sink to network edge. Because of having the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b9a64d2386aa7fec04fa0f2cbf5cb192
https://doi.org/10.1016/j.ins.2020.05.137
https://doi.org/10.1016/j.ins.2020.05.137
Publikováno v:
IEEE Transactions on Big Data. 6:131-144
Scheduling big data processing workflows involves both large-scale tasks and transmission of massive intermediate data among tasks, thus optimizing their completion time and monetary cost becomes a challenging issue. Besides, data streams are continu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cdff4fd1fed12495dc6216dfb120a26
https://doi.org/10.1109/tbdata.2018.2874469
https://doi.org/10.1109/tbdata.2018.2874469
Publikováno v:
Information Sciences. 509:457-469
Despite the recent development in evolutionary multi- and many-objective optimization, the problems with large-scale decision variables still remain challenging. In this work, we propose a scalable small subpopulations based covariance matrix adaptat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d737ef889fe787f73d4914d9dc45cce6
https://doi.org/10.1016/j.ins.2018.10.007
https://doi.org/10.1016/j.ins.2018.10.007