• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.111-120
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• 2009

The conceptual cost estimation used the construction project needs for confirm budget not only at the planning phase but also at the preliminary design phase of the construction project. Present, the conceptual cost estimation model have problems the rate of error is very large because the linear simple model calculate by use the cost of the unit meter or the unit square. This study development the model used grouping and the key quantity method, the mixed unit cost for solve problem of the very large rate of error. The result of this study reduced difference of between the real design construction cost therefor it expect that contribute to the client or the service company estimate budget of RC rahmen bridge.

• Korean Journal of Construction Engineering and Management
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• v.7 no.4 s.32
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• pp.91-99
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• 2006

The purpose of this study is propose an Artificial Neural Network(ANN) model for the construction estimate of the public educational facility at conceptual stage. The current method for the preliminary cost estimate of the public educational facility uses a single-parameter which is based on basic criteria such as a gross floor area. However, its accuracy is low due to the nature of the method. When the difference between the conceptual estimate and detailed estimate is huge, the project has to be modified to meet the established budget. Thus, the ANN model is developed by using multi-parameters in order to estimate the project budget cost more accurately. The result of the research shows 6.82% of the testing error rates when the developed model was tested. The error rates and the error range of the developed model are smaller than those of the general preliminary estimating model at conceptual stage. Since the proposed ANN model was trained using the detailed estimate information of the past 5 years' school construction data, it is expected to forecast the school project cost accurately.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.2
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• pp.781-790
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• 2013

This research focuses on development of the conceptual cost estimation models for I.L.M box girder bridge. The current conceptual cost estimation for public construction projects is dependent on governmental average unit price references which has been regarded as inaccurate and unreliable by many experts. Therefore, there have been strong demands for developing a better way of conceptual cost estimating methods. This research has proposed three different conceptual cost estimating method for a P.S.C. girder bridge built with the I.L.M method. Model (I) attempts to seek the proper breakdown of standard works that are accountable for more than 95 percentage in total cost and calculates the amount of standard work's materials from the standard section and volume of I.L.M box girder bridge. Model (II) utilizes a correlation analysis (coefficient over 0.6 or more) between breakdown of standard works and input data that would be considered available information in preliminary design phase. Model(III) obtains conceptual estimating through multiple-regression analysis between the breakdown of standard works and all of input data related to them. In order to validate the clustering of coverage in the preliminary design phase, the variation of I.L.M cost coverage from multiple-regression analysis[model(III)] has been investigated which result in between -3.76% and 11.79%, comparing with AACE(Association for the Advancement of Cost Engineering) which informs its variation between -5% and +15% in the design phase. The model proposed from this research are envisioned to be improved to a great distinct if reliable cost date for P.S.C. girder bridges can be continually collected with reasonable accuracies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.595-601
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• 2011

There is currently applied to the unit cost per a distance (KRW/km) for estimating the conceptual cost of civil work on basic planning stage of high speed railroad. This unit cost is an arithmetic average value based on historical data, which could be in big error. It also is difficult to explain the deficiency comparing the estimated cost derived from next basic design stage. This study provides the conceptual estimation model using by the parametric method and regression analysis. Independent variables are the distance and the geological materials (earth, weathered rock, soft-rock, hard-rock), extracting from the actual data to 36 contracts. The deviation between the unit costs estimated using the developed model and the actual cost data is presented in the range from -0.4% to +31%. This range is acceptable compared the typical range "-30% to + 50%". This model will improve the accuracy of existing method and be expected to contribute to effective total cost management and the economic aspects, reduce the financial expenditure.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1183-1188
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• 2009

Estimating project costs during the early stage of conceptual planning is very important when deciding whether to approve the project and allocate an appropriate budget. However, due to greater uncertainties involved in a project, it is challenging to estimate costs during this initial stage within a reasonable tolerance. This paper attempts to develop a cost-estimate model for public road projects under these circumstances and limitations. In the conceptual planning stage of a road project, there is only limited information for cost estimation, for example, such input data as total length of the route, origin and destination, number of lanes, general geographic characteristics of the route, and other basic attributes. This implies that the model should individuate suitable but restricted information without considering detailed features such as quantity of earthwork and a detailed route of a given condition. With these limited facts, this paper applies a case-based reasoning (CBR) method to solve a new problem by deriving similar past problems, which in turn is used to estimate the cost of a given project based on best-fitted previous cases. To develop a CBR cost-estimate model, the authors classified 8 representative variables, including project type, the number of lanes, total length, road design grades, etc. Then, we developed the CBR model, primarily by using 180 actual cases of public road projects, procured over the last decade. With the CBR model, it was found that the degree of error in estimation can be reasonably reduced, to below approximately 30% compared to the final costs estimated upon the completion of detailed design.

• Korean Journal of Construction Engineering and Management
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• v.15 no.2
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• pp.53-61
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• 2014

Previous studies reveal the need for a tool to cost estimation of building design in early design stages. This paper proposes an internal finishes cost model tool to address this need. The tool allows users to evaluate the functionality, economics and quality of finishes concurrently with high-rise building design. Lack of information in the early stages of the project enables a relatively accurate estimates of work to raise up. Measurements are automatically extracted from simple design information and profile driven estimates are revised in real-time. The data model uses a flexible unit rate system that can easily be extended to other estimate dimensions such as mix-use building surcharge rate estimation. The approach illustrated in this paper is applicable to BIM tool conceptual estimation that support for massing purposes other than the one chosen for this study.

• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.495-506
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• 2021

A Conceptual cost estimate, which is computed in the preliminary step of a project, is important for decision-making by a contractor in terms of the project budget, economic feasibility and validity analysis, and alternative comparisons. Therefore, a high error rate of a prediction model for a conceptual cost estimate can lead to various problems including excessive project expenditures and a delayed break-even point. this study proposed optimal impact factors by configuring quantitative impact factors computable in a preliminary step in various cases(combinations of impact factors). subsequently, the accuracy of different cases was comparatively analyzed by using the cases as input values of a prediction model using regression analysis. when the optimal combination of impact factors proposed in this study and other combination of impact factors were applied to the prediction model, the regression analysis-based prediction model exhibited 0.2-4.7% improvements in accuracy, respectively. the optimal combination of impact factors proposed in this study improved the accuracy of the prediction model of a conceptual cost estimate by removing unnecessary impact factor.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.417-424
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• 2009

For a construction project to progress smoothly, effective cost estimation is vital, particularly in the conceptual and schematic design stages. In these early phases, despite the fact that initial estimates are highly sensitive to changes in project scope, owners require accurate forecasts which reflect their supplying information. Thus, cost estimators need effective estimation strategies. Practically, parametric cost estimates are the most commonly used method in these initial phases, which utilizes historical cost data (Karshenas 1984, Kirkham 2007). Hence, compilation of historical data regarding appropriate cost variance governing parameters is a prime requirement. However, precedent practice of data mining (data preprocessing) for denoising internal errors or abnormal values is needed before compilation. As an effort to deal with this issue, this research proposed a statistical methodology for data preprocessing and verified that data preprocessing has a positive impact on the enhancement of estimate accuracy and stability. Moreover, Statistically Preprocessed data Based Parametric (SPBP) cost models are developed based on multiple regression equations and verified their effectiveness compared with conventional cost models.

• Journal of the military operations research society of Korea
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• v.27 no.1
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• pp.10-27
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• 2001

This paper deals with the application of PRICE model in estimating the proper acquisition cost for weapon budgeting phase. The PRICE(Parametric Review of Information for Costing and Evaluation) Hardware model is a computerized method for deriving cost estimates of electronic and mechanical hardware assemblies and systems. The model can be used in obtaining not only initial cost estimates in conceptual phase, but also detailed cost estimates in budgeting phase depending on available historical and empirical data. We analyzed first step cost estimate parameters and derived cost equations using PRICe output dta. Using weight and complexity, We can find cost variation. Sensitivity analysis shows that cost increases exponentially as complexity increases exponentially as complexity increases. We estimated KAAV\`s (Korea Amphibious Assault Vehicle) production cost using the PRICE model and compare with engineering cost estimates which is based on actual production data submitted by the production company. The result shows that tow estimates are close within $\pm2%$ differences.

• Korean Journal of Construction Engineering and Management
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• v.9 no.2
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• pp.170-181
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• 2008

Cost of construction project have to be estimated based on drawing before execution. Cost estimate and check would be performed numerously for preparing general outline of requirements and determining the budget at conceptual planning stage, for obtaining decision on every matter related to design, specification, construction and cost at design stage, and for predicting bidding cost. Thus, importance of cost estimation cannot emphasize too much in construction. However, there are lack of standard estimation method, process, and cost analysis method, that square foot estimation method is as used as eyer, in Korea. Thus, This research present the direction for improving cost estimation and management in construction; It is demanded that establishing standard data base methodology, multi-level database model CUBE, and standard cost planning process, choosing cost estimation methodology according to objectives and cost planning process, and making more experts.