Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Runxiu Wu"'
Publikováno v:
Entropy, Vol 25, Iss 3, p 480 (2023)
Tri-training expands the training set by adding pseudo-labels to unlabeled data, which effectively improves the generalization ability of the classifier, but it is easy to mislabel unlabeled data into training noise, which damages the learning effici
Externí odkaz:
https://doaj.org/article/42ac0d5660cb44a8adba06fb24a5ce45
Publikováno v:
Concurrency and Computation: Practice and Experience. 35
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6c127ec3899de2840666a8f0024ea77c
https://doi.org/10.1002/cpe.7496
https://doi.org/10.1002/cpe.7496
Publikováno v:
Mathematics, Vol 7, Iss 3, p 289 (2019)
Artificial bee colony is a powerful optimization method, which has strong search abilities to solve many optimization problems. However, some studies proved that ABC has poor exploitation abilities in complex optimization problems. To overcome this i
Externí odkaz:
https://doaj.org/article/1934f3a091a34b92b0b5568107219a78
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811680472
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::01c7f19cbf30771571a9eb40d397411e
https://doi.org/10.1007/978-981-16-8048-9_13
https://doi.org/10.1007/978-981-16-8048-9_13
Publikováno v:
KSII Transactions on Internet & Information Systems; Dec2022, Vol. 16 Issue 12, p3889-3903, 15p
Publikováno v:
International Journal of Innovative Computing and Applications. 13:351
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e15471a113d2c5fddf44b42fa4fccd4
https://doi.org/10.1504/ijica.2022.128442
https://doi.org/10.1504/ijica.2022.128442
Publikováno v:
International Journal of Computing Science and Mathematics. 16:355
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::283bf7d6ea64fe9e4d5bd3771f1b2f81
https://doi.org/10.1504/ijcsm.2022.10053741
https://doi.org/10.1504/ijcsm.2022.10053741
Publikováno v:
International Journal of Bio-Inspired Computation. 17:24
Density peaks clustering algorithm uses Euclidean distance as a measure of similarity between the samples and it can achieve a good clustering effect when processing the manifold datasets. Utilising this feature, we propose a density peaks clustering
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3298e18f83d2f63f6fe26fb9190814fe
https://doi.org/10.1504/ijbic.2021.10035837
https://doi.org/10.1504/ijbic.2021.10035837
Publikováno v:
International Journal of Computing Science and Mathematics. 12:1
Density peaks clustering (DPC) determines the density peaks according to density-distance, and local density computation significantly impacts the clustering performance of the DPC algorithm. Following this lead, a revised DPC algorithm based on cosi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94d16e27d3ca7a794c19fd8ca9f3b669
https://doi.org/10.1504/ijcsm.2020.10030824
https://doi.org/10.1504/ijcsm.2020.10030824
Publikováno v:
International Journal of Computing Science and Mathematics. 12:309
The particles in the population of the firefly algorithm learn from each other using an all-attractive model, and the algorithm has a strong ability of social learning and global detection. However, the algorithm ignores the role of the global optima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4bf406305ade4092cc81115a88a616cc
https://doi.org/10.1504/ijcsm.2020.112674
https://doi.org/10.1504/ijcsm.2020.112674