An optimization method for learning statistical classifiers in structural reliability

Probabilistic Engineering Mechanics

Volumn 25, Issue 1, 2010, Pages 26-34

  Hurtado, Jorge E ^a   Alvarez, Diego A ^a  

^a UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

Author keywords

Entropy; Monte Carlo simulation; Neural networks; Particle swarm optimization; Quasi random numbers; Statistical classification; Structural reliability; Support vector machines

Indexed keywords

CLASSIFICATION APPROACH; COMPUTATIONAL EFFORT; CRITICAL STEPS; DISTINCTIVE FEATURES; FUNCTION APPROXIMATION; GENERALIZATION CAPACITY; LEARNING SAMPLES; LIMIT STATE FUNCTIONS; MONTE CARLO SIMULATION; OPTIMIZATION METHOD; PROBABILITY OF FAILURE; QUASI-RANDOM; QUASI-RANDOM NUMBERS; RESPONSE SURFACE METHOD; ROBUST METHODS; STATISTICAL CLASSIFICATION; STATISTICAL CLASSIFICATION TECHNIQUES; STATISTICAL CLASSIFIER; STATISTICAL LEARNING; STRUCTURAL RELIABILITY; STRUCTURAL RELIABILITY ANALYSIS; SVM CLASSIFIERS;

CLASSIFIERS; COMPUTATIONAL EFFICIENCY; COMPUTER SIMULATION; COSMIC RAY DETECTORS; EDUCATION; IMAGE RETRIEVAL; MONTE CARLO METHODS; NEURAL NETWORKS; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; QUALITY ASSURANCE; RANDOM NUMBER GENERATION; RELIABILITY ANALYSIS; SHAPE OPTIMIZATION; SUPPORT VECTOR MACHINES;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 70349929280     PISSN: 02668920     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.probengmech.2009.05.006     Document Type: Article

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