University of Aberdeen logo

AURA - Aberdeen University Research Archive

 

Gravitation Field Algorithm with Optimal Detection for Unconstrained Optimization

dc.contributor.authorHuang, Lan
dc.contributor.authorHu, Xuemei
dc.contributor.authorWang, Yan
dc.contributor.authorZhang, Fang
dc.contributor.authorLiu , Zhendong
dc.contributor.authorPang, Wei
dc.contributor.institutionUniversity of Aberdeen.Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.contributor.institutionUniversity of Aberdeen.Computing Scienceen
dc.date.accessioned2017-12-06T17:47:37Z
dc.date.available2017-12-06T17:47:37Z
dc.date.issued2017
dc.descriptionThis work is supported by the National Natural Science Foundation of China (Grant Nos. 61472159, 61572227), Development Project of Jilin Province of China (Nos. 20160204022GX, 20160414009GH, 2017C033).en
dc.format.extent6
dc.format.extent1440101
dc.identifier112378878
dc.identifiereb24cead-5b33-4b8a-97c2-02ec02af8f66
dc.identifier85046653313
dc.identifier.citationHuang, L, Hu, X, Wang, Y, Zhang, F, Liu , Z & Pang, W 2017, Gravitation Field Algorithm with Optimal Detection for Unconstrained Optimization. in The 2017 4th International Conference on Systems and Informatics (ICSAI 2017). IEEE Press, pp. 1328-1333, The 2017 4th International Conference on Systems and Informatics , Hangzhou Zhejiang, China, 11/11/17.en
dc.identifier.citationconferenceen
dc.identifier.isbn978-1-5386-1106-7
dc.identifier.otherORCID: /0000-0002-1761-6659/work/52133908
dc.identifier.otherORCID: /0000-0002-1761-6659/work/59923294
dc.identifier.urihttp://hdl.handle.net/2164/9736
dc.language.isoeng
dc.publisherIEEE Press
dc.relation.ispartofThe 2017 4th International Conference on Systems and Informatics (ICSAI 2017)en
dc.subjectgravitation field algorithmen
dc.subjectoptimal detectionen
dc.subjectunconstraint optimizationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subject.lccQA75en
dc.titleGravitation Field Algorithm with Optimal Detection for Unconstrained Optimizationen
dc.typeConference itemen

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
ICSAI_20171023hxm_finalaccepted.pdf
Size:
1.37 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
8.29 KB
Format:
Plain Text
Description: