The approximate cost estimating model for railway bridge project in the planning phase using CBR method

The budget estimated in the planning phase of construction has to be accurate to be effective until after the design phase. Therefore the special method needs to improve the accuracy of estimating construction cost in the planning phase. Recently, to improve the accuracy of estimating construction cost for road bridges and architectural facilities, Case-based Reasoning (CBR) which makes use of Genetic Algorithm (GA) and Multiple Regression Analysis (MRA) and other principles are being used. This study suggests the cost estimation model which uses CBR and makes the database reflected the character of the railroad bridge. To establish this effective CBR model, this study examined combinations of attributes, criteria of similarities and retrieval ranks and applied GA for an optimization of attribute weights throughout learning process. According to the results of this study, CBR should use a five-attribute combination, retrieve six similar cases and use the similarity criteria by applying a method in which ten points are deducted for each 10% difference to get the minimum error. According to the verification results of the CBR model, the mean absolute error rate is 11. 9% and the standard deviation is 12. 7%. Therefore, the accuracy of this CBR model is 30% more effective than the criteria of Ministry of Construction & Transportation (MOCT) and Korea Development Institute (KDI) model.