Difference between revisions of "Bibliography:HighlyCited"
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pages = 617-629 | | pages = 617-629 | | ||
− | doi = 10.1007/s00500-006-0124-0}} | + | doi = [10.1007/s00500-006-0124-0]]. Citations: [http://isiknowledge.com/ Web of Science] - 24, [http://www.scopus.com/ Scopus] - 30, [http://scholar.google.com/scholar?hl=en&lr=&ie=UTF-8&inlang=pl&cites=12517123885220928578 Google Scholar] - 38; [http://labs.researcherid.com/mashlets/rid/mashletsServer.jsp?rid=B-8013-2008&mid=CitationDistribution&cat=Categories Citing Network]}} |
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− | doi = 10.1007/s10489-007-0091-x}} | + | doi = [10.1007/s10489-007-0091-x]]. Citations: [http://isiknowledge.com/ Web of Science] - 11, [http://www.scopus.com/ Scopus] - 9, [http://scholar.google.com/scholar?hl=en&lr=&ie=UTF-8&inlang=pl&cites=12517123885220928578 Google Scholar] - 26; [http://labs.researcherid.com/mashlets/rid/mashletsServer.jsp?rid=B-8013-2008&mid=CitationDistribution&cat=Categories Citing Network]}} |
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Revision as of 08:34, 6 August 2010
(pdf) J. Brest, S. Greiner, B. Bošković, M. Mernik, V. Žumer. Self-Adapting Control Parameters in Differential Evolution: A Comparative Study on Numerical Benchmark Problems. IEEE Transactions on Evolutionary Computation, 2006, volume 10, issue 6, pp. 646-657. DOI [10.1109/TEVC.2006.872133]. Citations: Web of Science - 90, Scopus - 123, Google Scholar - 147; Citing Network [10.1109/TEVC.2006.872133]]. Citations: Web of Science - 90, Scopus - 123, Google Scholar - 147; Citing Network]. |
(pdf) J. Brest, B. Bošković, S. Greiner, V. Žumer, M. S. Maučec. Performance comparison of self-adaptive and adaptive differential evolution algorithms. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2007, volume 11, issue 7, pp. 617-629. DOI [10.1007/s00500-006-0124-0]. Citations: Web of Science - 24, Scopus - 30, Google Scholar - 38; Citing Network [10.1007/s00500-006-0124-0]]. Citations: Web of Science - 24, Scopus - 30, Google Scholar - 38; Citing Network]. |
(pdf) J. Brest, M. S. Maučec. Population Size Reduction for the Differential Evolution Algorithm. Applied Intelligence, 2008, volume 29, issue 3, pp. 228-247. DOI [10.1007/s10489-007-0091-x]. Citations: Web of Science - 11, Scopus - 9, Google Scholar - 26; Citing Network [10.1007/s10489-007-0091-x]]. Citations: Web of Science - 11, Scopus - 9, Google Scholar - 26; Citing Network]. |