• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.423-426
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• 2002

The foundation for developing a cost estimation system based on historical data has been being prepared in Korea. Historical data is a priori of developing a cost estimation model. Cost Index, one of the historical data, is used to estimate construction cost and to adjust the amount of contract money in the foreign country, whereas it is not used in domestic except for the road construction project in Korea. Construction cost indices can be used by an estimator in tender analysis, pricing, price adjustment, cost planning, and forecasting. In this regards, this paper identified the problems in developing Cost Index evaluation process by comparing the standard of framing Cost Index used in British to the one used in Korea. Then, the scheme for improving a Cost Index required for Site Developing Construction was proposed. Twenty-two cases of engineering estimate data were used to compare the domestic standard to the foreign one in deriving a Cost Index.

• IE interfaces
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• v.4 no.1
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• pp.35-46
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• 1991

The purpose of this paper is to present how to prepare pro forma manufacturing cost, and profit and loss statements using the historical data of the industry to which the project under consideration belong to. This approach is proposed because it is relatively simple compared with possible alternative methods. The approach proposed here can be used in countries other than Korean if relevant historical data is available. An example is shown.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.256-260
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• 2004

As a large portion of defence budget are alloted for military facility construction, reasonable budget estimation in the planning stage has been officers' main concerns. However the proper estimation of construction cost is difficult to be carried out due to the absence of systematic criteria. To improve the budget estimation for military facility construction, this study proposes a cost index model which can convert historical cost to current cost. Thus the developed cost index would enhance effectiveness of budget estimation process 3nd support reasonable decision making. This cost index model is developed by analyzing historical cost data with statistical methodology The study is executed by following process. First, factors which affect construction cost for the most are selected by analyzing historical cost data. second, the selected factors are categorized material cost, labor cost and equipment cost, and weights of those factors are calculated by dividing the cost of each factor by total item costs. Last, cost index is developed by using weighted average method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.119-126
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• 2004

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristic. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• IE interfaces
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• v.18 no.4
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• pp.382-389
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• 2005

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristics. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• Korean Journal of Construction Engineering and Management
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• v.4 no.4 s.16
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• pp.192-200
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• 2003

The object of this research is to develop a computerized algorithm of cost estimation method to forecast the total construction cost in the bidding stage by the historical and elemental work cost data. Traditional cost models to prepare Bill of Quantities in the korea construction industry since 1970 are not helpful to forecast the project total cost in the bidding stage because the BOQ is always constant data according to the design factors of a particular project. On the contrary, statistical models can provide cost quicker and more reliable than traditional ones if the collected cost data are sufficient enough to analyze the trends of the variables. The estimation system considers non-deterministic methods which referred to as the 'Monte Carlo simulation. The method interprets cost data to generate a probabilistic distribution for total costs from the deficient elemental experience cost distribution.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.540-545
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• 2008

The purpose of this study is to suggest problems and improving plan of process of calculating escalation rate of the Historical Cost by price fluctuation. In order to implement this research, we analyzed problems by calculating the rate of price fluctuation with Historical Cost and measurement applying method making on-site with historical cost data were included as samples and suggested improving plan to the adjustment of contract cost. The results of research according to this are same as followings:1) Of all construction details, it is more appropriate to calculate price fluctuation by applying measurement method to the contents of historical cost unit. 2) To avoid confusion in calculating method, it was indicated that amendment in part should be achieved in order to calculate by measuring the part of calculating escalation rate of Historical Cost at related law and regulation.

• Journal of the Korea Institute of Building Construction
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• v.14 no.5
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• pp.477-485
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• 2014

Standard production unit system and historical cost data are the most typical data base for calculating budget price in construction. However, these construction cost estimation methods are difficult to calculate proper construction cost because definition, additional allowance or modification criteria is not clear in construction within one day. Therefore, this study identifies problems for standard production unit system and historical cost data and suggests the improvements for them. For the objectives, this study analyzes frequency after implementing survey for 44 specialty contractors in placing at kyeonggi-province. As the results of the study, labor costs in standard production unit system and equipment costs in historical cost data and in construction of pavement and maintenance by project type was exceeded at most high rate against construction cost estimation methods. Based on this result, standard production unit system and historical cost data need to be modified by three improvements such as classification by project scale. These will be baseline data for improvement of construction cost estimation methods for less than one day workload.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.3
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• pp.51-61
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• 2014

In this paper, we deal with developing a cost estimation relationships (CER) for Korean maneuverable weapons systems using historical production cost. To develop the CER, we collected the historical data of the production cost of four tanks and five armored vehicles. We also analyzed the Required Operational Capability (ROC) of the weapons systems and chose cost drivers that can compare operational capabilities of the weapons systems We used Forward selection, Backward selection, Stepwise Regression and $R^2$ selection as the cost drivers which have the greatest influence with the dependent variables. And we used Principle Component Regression, Robust Regression and Weighted Regression to deal with multicollinearity and outlier among the data to develop a more appropriate CER. As a result, we were able to develop a production cost CER for Korean maneuverable weapons systems that have the lowest cost errors. Thus, this research is meaningful in terms of developing a CER based on Korean original cost data without foreign data and these methods will contribute to developing a Korean cost analysis program in the future.

• Journal of Korean Society of Rural Planning
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• v.2 no.2
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• pp.103-108
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• 1996

In rural planning, the cost estimation of project is a key factor for planning. Therefore, development of reliable cost estimation method is essential. Recently, new techniques are suggested for determination of project cost using historical cost data. In this study, a multiple-regression analysis was used to determine the cost of the farm land consolidation. The results demonstrated that multiple regression analysis using historical cost data can be applicable to project cost estimation.