A GA-PCA approach for power sector performance ranking based on machine productivity

Applied Mathematics and Computation

Volumn 186, Issue 2, 2007, Pages 1205-1215

  Ebrahimipour, V ^a,b   Azadeh, A ^b   Rezaie, K ^b   Suzuki, K ^a  

^a OKAYAMA UNIVERSITY   (Japan)

^b UNIVERSITY OF TEHRAN   (Iran)

Author keywords

Genetic Algorithms; Numerical Taxonomy; Principle Component Analysis; Productivity

Indexed keywords

CORRELATION METHODS; ELECTRIC MACHINE THEORY; GENETIC ALGORITHMS; PRINCIPAL COMPONENT ANALYSIS; PRODUCTIVITY; PROFITABILITY; TAXONOMIES;

CORRELATION EXPERIMENTS; DEGREE OF CORRELATION; MACHINERY PRODUCTIVITY INDICATORS; NUMERICAL TAXONOMY (NT);

ELECTRIC POWER SYSTEMS;

EID: 33947699441     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2006.07.138     Document Type: Article

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