Zobrazeno 1 - 10
of 187
pro vyhledávání: '"Mean field annealing"'
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2003 Oct . 100(21), 11936-11940.
Externí odkaz:
https://www.jstor.org/stable/3147884
Publikováno v:
Operations Research Letters. 48:271-277
It is shown that certain general classes of constrained binary optimization tasks can be solved with increasing accuracy by a first order mean field approximation of the Boltzmann distribution of the associated Lagrangian as the instance size grows.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c6aaa482988a3ab2f9fccbcb9378e15
https://doi.org/10.1016/j.orl.2020.03.002
https://doi.org/10.1016/j.orl.2020.03.002
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Abdel-Qader Ikhlas, Bujanovic Tomislav
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2005, Iss 12, p 290134 (2005)
Segmentation and motion estimation are two problems that require accurate estimation for many applications in computer vision and image analysis. This work presents a solution to these two problems simultaneously. Both the segmentation and motion fie
Externí odkaz:
https://doaj.org/article/b0476449a8d74c0f9ff29265f5d5371f
Autor:
Yeongjoon Kim, Chuleui Hong
Publikováno v:
International Journal of Software Engineering and Its Applications. 8:315-322
Mean Field Genetic Algorithm (MGA) is a hybrid algorithm of Mean Field Annealing (MFA) and Simulated annealing-like Genetic Algorithm (SGA). It combines benefit of rapid convergence property of MFA and effective genetic operations of SGA. This paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c333e272f53c86520d2b3da7681ba792
https://doi.org/10.14257/ijseia.2014.8.1.27
https://doi.org/10.14257/ijseia.2014.8.1.27
Publikováno v:
ETRI Journal. 32:932-939
In this paper, a fast migration method is proposed. Our method executes local relocation on a model placement where an additional module is added to it for modification with a minimum number of displacements. This method is based on mean-field anneal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b1ff7767792f9adcd45a231f18bb3e3
https://doi.org/10.4218/etrij.10.0109.0533
https://doi.org/10.4218/etrij.10.0109.0533
Publikováno v:
Molecular Ecology Resources. 11:116-125
We describe a distance-based clustering method using a proximity matrix of genetic distances to partition populations into genetically similar groupings. The optimization heuristic mean-field annealing (MFA) was used to find locally optimal solutions
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e92e627c83d886c09d6c1fda429c1e2b
https://doi.org/10.1111/j.1755-0998.2010.02902.x
https://doi.org/10.1111/j.1755-0998.2010.02902.x
Autor:
Chul-Eui Hong
Publikováno v:
Journal of information and communication convergence engineering. 8:13-18
The composite stock cutting problem is defined as allocating rectangular and irregular patterns onto a large composite stock sheet of finite dimensions in such a way that the resulting scrap will be minimized. In this paper, we introduce a novel appr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c81f287689df0037d310b6768a5e3e1a
https://doi.org/10.6109/jicce.2010.8.1.013
https://doi.org/10.6109/jicce.2010.8.1.013
Publikováno v:
Computers & Mathematics with Applications. 57:970-980
In this paper, we propose an unsupervised segmentation algorithm for color images based on Gaussian mixture models (GMMs). The number of mixture components is determined automatically by adaptive mean shift, in which local clusters are estimated by r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61b2451183fca15bca230958ea988228
https://doi.org/10.1016/j.camwa.2008.10.053
https://doi.org/10.1016/j.camwa.2008.10.053