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Volumn , Issue , 2011, Pages 1239-1246

Studying the behavior of a multiobjective genetic algorithm to design fuzzy rule-based classification systems for imbalanced data-sets

Author keywords

feature selection; Fuzzy Rule Based Classification Systems; granularity level; imbalanced data sets; Multiobjective Genetic Algorithms

Indexed keywords

CLASS DISTRIBUTIONS; EXPERIMENTAL ANALYSIS; FUZZY RULE BASED CLASSIFICATION SYSTEMS; GRANULARITY LEVELS; IMBALANCED DATA-SETS; LOW COMPLEXITY; MULTI-OBJECTIVE GENETIC ALGORITHM; MULTIOBJECTIVE APPROACH; OPEN PROBLEMS; REAL APPLICATIONS; SINGLE-OBJECTIVE GENETIC ALGORITHMS;

EID: 80053085826     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2011.6007436     Document Type: Conference Paper
Times cited : (6)

References (8)
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    • Denis, N.J.1
  • 4
    • 0030290822 scopus 로고    scopus 로고
    • Modified recursive maximum likehood adaptive filter for nonlinear aircraft flight path reconstruction
    • Q. P., Chu, J. A., Mulder, and P. T. L. M., van Woerkom, "Modified recursive maximum likehood adaptive filter for nonlinear aircraft flight path reconstruction," J. Guidance, Contr., and Dyn., vol 19, no 6, pp.1285-1295, 1996.
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  • 6
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  • 8
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    • Trajectory reconstruction during thrusting phase of rockets using differential corrections
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.