CORRELATION TOLERANCE LIMIT SETTING SYSTEM USING REPETITIVE CROSS-VALIDATION AND METHOD THEREFOR

摘要

The present invention relates to a correlation tolerance limit setting system using repetitive cross-validation and a method therefor and, to a correlation tolerance limit setting system using repetitive cross-validation and a method therefor, the system and the method being for preventing data characteristic distortion due to accidental or human interference in correlation optimization and tolerance limit setting, and for preventing a risk created thereby, or for quantifying the influence thereof. According to the present invention, the correlation tolerance limit setting system using repetitive cross-validation comprises: a variable extraction unit for classifying training sets and validation sets, and optimizing a correlation coefficient so as to extract variables; a normality verification unit for verifying normality in accordance with the variable extraction resu a DNBR limit unit for verifying whether the same population is present according to the normality, and determining a tolerance limit of a departure from a nucleate boiling ratio by using a tolerance limit distribution for a departure from nucleate boiling; and a control unit.