Data imputing uses to posit missing data values, as missing data have a negative effect on the computation validity of models. This study develops a genetic algorithm (GA) to optimize imputing for missing cost data of fans used in road tunnels by the Swedish Transport Administration (Trafikverket). GA uses to impute the missing cost data using an optimized valid data period. The results show highly correlated data (R- squared 0.99) after imputing the missing data. Therefore, GA provides a wide search space to optimize imputing and create complete data. The complete data can be used for forecasting and life cycle cost analysis.
data imputing, genetic algorithms (GA), R-Squared
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