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Volumn , Issue , 2004, Pages

On the use of surrogate evaluation models in multi-objective evolutionary algorithms

Author keywords

Evolutionary algorithms; Metamodel assisted optimization; Multi objective optimization; Radial basis function networks; Self organizing maps

Indexed keywords

APPROXIMATION MODEL; COMPUTATIONAL COSTS; EVOLUTIONARY OPTIMIZATIONS; IMPLEMENTATION SCHEME; METAMODEL-ASSISTED OPTIMIZATIONS; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; PREDICTION CAPABILITY;

EID: 66749115218     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (17)
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    • Giotis, A.P.1    Giannakoglou, K.C.2    Périaux, J.3
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    • Giannakoglou, K.C.1    Giotis, A.P.2    Karakasis, M.K.3
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    • Design of optimal aerodynamic shapes using stochastic optimization methods and computational intelligence
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    • Giannakoglou, K.C.1
  • 9
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    • Sedgewick, R.1
  • 14
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    • Networks for approximation and learning
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    • Poggio, T.1    Girosi, F.2
  • 15
    • 0031270611 scopus 로고    scopus 로고
    • Growing radial basis neural networks: Merging supervised and unsupervised learning with network growth techniques
    • November
    • N. Karayiannis and W. M. Glenn. Growing radial basis neural networks: Merging supervised and unsupervised learning with network growth techniques. IEEE Transactions on Neural Networks, 8(6):1492-1506, November 1997.
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    • Karayiannis, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.