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Volumn 155, Issue , 2008, Pages 11-28

Opposition-based computing

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EID: 51649122519     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-70829-2_2     Document Type: Article
Times cited : (26)

References (23)
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    • Neural Network Learning Using Low-Discrepancy Sequence
    • Foo, N.Y, ed, Canadian AI 1999, Springer, Heidelberg
    • Jordanov, I., Brown, R.: Neural Network Learning Using Low-Discrepancy Sequence. In: Foo, N.Y. (ed.) Canadian AI 1999. LNCS, vol. 1747, pp. 255-267. Springer, Heidelberg (1999)
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    • Jordanov, I.1    Brown, R.2
  • 8
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    • Application of Quasi Monte Carlo Methods in Global Optimization
    • Kucherenko, S.: Application of Quasi Monte Carlo Methods in Global Optimization. In: Global Optimization, pp. 111-133 (2006)
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  • 9
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    • Application of Deterministic Low-Discrepancy Sequences in Global Optimization
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  • 12
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    • On Initial Populations of a Genetic Algorithm for Continuous Optimization Problems
    • Maaranen, H., Miettinen, K., Penttinen, A.: On Initial Populations of a Genetic Algorithm for Continuous Optimization Problems. Journal of Global Optimization 37, 405-436 (2007)
    • (2007) Journal of Global Optimization , vol.37 , pp. 405-436
    • Maaranen, H.1    Miettinen, K.2    Penttinen, A.3
  • 13
    • 77949628825 scopus 로고    scopus 로고
    • Initialising PSO with Randomised Low-Discrepancy Sequences: The Comparative Results
    • Nguyen, Q., Nguyen, X., McKay, R., Tuan, P.: Initialising PSO with Randomised Low-Discrepancy Sequences: The Comparative Results. In: Congress on Evolutionary Computation, pp. 1985-1992 (2007)
    • (2007) Congress on Evolutionary Computation , pp. 1985-1992
    • Nguyen, Q.1    Nguyen, X.2    McKay, R.3    Tuan, P.4
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    • Optimization of Functions by Quasi-random Search Methods
    • Niederreiter, H., McCurley, K.: Optimization of Functions by Quasi-random Search Methods. Computing 22(2), 119-123 (1979)
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    • A Novel Population Initialization Method for Accelerating Evolutionary Algorithms
    • Rahnamayan, S., Tizhoosh, H.R., Salamaa, M.: A Novel Population Initialization Method for Accelerating Evolutionary Algorithms. Computers and Mathematics with Applications 53(10), 1605-1614 (2007)
    • (2007) Computers and Mathematics with Applications , vol.53 , Issue.10 , pp. 1605-1614
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  • 18
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    • Opposition versus randomness in soft computing techniques
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    • Similarity and dissimilarity as evidence in perceptual categorization
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    • Stewart, N.1    Brown, G.D.A.2
  • 23
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    • On the Convergence of Sequential Number-Theoretic Method for Optimization
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    • Yaochen, Z.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.