• Proceedings of the Korea Society for Simulation Conference
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• 1998.03a
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• pp.61-64
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• 1998

도로의 건설을 위해서는 통상 타당성조사, 기본계획, 기본설계 및 시공의 여러 가지 단계를 밟는다. 이들 각 단계를 거치면서 일반적으로 투자비 추정액은 실제 공사비와 더욱 근접하게 되게 되나, 타당성조사 등 계획단계에서의 추정액은 실제 공사비와 상당한 차이를 보이는 것이 일반적이다. 이러한 차이는 계획물량의 추정이나, 단가의 추정 등에서도 발생할 수도 있고, 구체적인 지질조사 등이 없는 상태에서 가정한 지질조건이나 공사조건 등에 대한 불확실성으로 인해 발생한다. 현재의 일반적인 관행은 이러한 투자비 추정단계에 작용하는 불확실성을 명시적으로 고려하여 투자비 추정치의 확률적인 분포를 산정하지 않고, 하나의 확정적인 추정치만 제시하고 있어 제시된 추정치의 신뢰도를 확인하기가 곤란하다. 본 연구에서는 현재의 관행과는 달리 투자비추정에서 관여하는 불확실성을 확률분포를 사용하여 명시적으로 고려하여 추정된 투자비에 대한 확률분포를 명시적으로 파악하려는 노력을 하였다. 추정된 투자비에 대한 확률분포는 Mont Carlo 시뮬레이션 방법을 이용하여 분석하였으며, 연구의 결과와 현재 각 계획단계에서 일반적으로 용인되는 추정오차와의 관계도 분석하였다. 결과에 근거하여 도로사업에 대한 투자비 추정을 효율적으로 할 수 있는 방법을 제시하였으며, 추가적인 연구방향도 제시하였다.

• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.55-65
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• 2010

To effectively secure and execute the national budget, it is very important to estimate the reasonable construction cost of each process in the construction of public facilities and works. The construction cost is generally estimated at the time when the design of the targeted structures has been completed. Without detailed sectional drawings and with only simple information on bridge structures in the planning stage or in the early design stage. it would be very difficult to predict the approximate construction cost. In this study, a more efficient and appropriate approximate construction cost estimation model in the planning stage and in the early design stage is presented and verified as reliable by analyzing the construction cost data of 61 existing steel box girder bridges from previous studies. The results of this study show that when the construction cost that was predicted using the construction cost estimation model in the design stage was compared with the cost from the conventional standards, the suggested model in this study produced results with a very high confidence level.

• Journal of the Society of Disaster Information
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• v.9 no.1
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• pp.11-21
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• 2013

This study proposed cost prediction equation model by considering duration, construction, size, actual cost with the subway construction started by the actual cost system which was introduced since 2004. Costs - scale exponent n(confidence range: 0.5 to 0.7) for cost prediction of subway construction was drawn total cost(0.713), net cost(0.77) in point of the 11 subway construction data. The cost prediction equation model of the subway construction which was presented in this study is able to effectively apply to business planning, preliminary investigation, feasibility study, basic design stage to estimate the approximate cost in the future.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.553-556
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• 2009

최근 우리나라의 건설 분야에서는 생애주기비용(Life Cycle Cost;이하 LCC)/가치공학(Value Engineering; 이하 VE)을 적용한 구조물 설계가 실시되고 있다. 이는, 건설교통부에서 공공건설사업의 효율성을 제고하기 위하여 실시하고 있으며, 대통령령에 따라 "건설기술관리법시행령"을 제정하여 공공사업분 수행 절차와 기준을 법제화 하였으며 이후 시행령 38조 13의 "설계의 경제성등 검토" 실시를 의무화하는 시행지침을 작성하여 수행하고 있다. 이러한, LCC/VE의 검토에서 보수 보강 공사비 산정은 유지보수공사 프로파일링을 통한 보수 보강 시기를 산정(건설교통부, 2003)하여 교량 구성요소별 보수 교체 주기를 산정(건설교통부, 2001)에서 제시한 기간을 적용하여 LCC/VE를 평가하고 있다. 하지만, 이러한 보수 보강 공사비의 적용은 일괄적인 적용이며, 예전 국내의 교량 건설기술이 현재와 같이 발전된 상태에서의 현황이 아니므로 본 연구에서는 현재 고속국도에 완공되어 운용중인 교량 구조물을 시설물의 안전관리에 관한 특별법 시행령(2008)에 따른 "시설물의 안전점검 및 정밀안전진단 지침"에 의한 교량의 초기점검, 정밀점검 및 정밀안전진단 자료를 조사 분석하여 보수 보강 공사비 곡선을 추정하려 한다.

• 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.

• Korean Journal of Construction Engineering and Management
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• v.9 no.3
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• pp.65-74
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• 2008

Public institutions recognize the importance of cost management from the planning stage but they do not have an organized construction cost estimation and management system. Thus, at the stage of planning a new public construction project and estimating the cost, those in charge of budgeting estimate construction cost based on existing data and experiences, compare construction cost estimated after the basic design stage and the execution design stage with budgets, and then decide whether to continue the project or change the design according to the budgets. Therefore, we would develop the cost prediction model through regression analysis that can predict construction cost in Schematic Design Phase of the Public Multi-Family housing. Accordingly, if public institutions have a construction cost prediction model and management system that can estimate the optimum construction cost, they can make and execute budgets in a more efficient way than they do at present.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.274-277
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• 2006

The EAC(Estimate at Completion) among existing methods, which estimate cost and time effectively, help managers anticipate changeable several results at the point of $15{\sim}30%$ in the project progress. However, this method may cause such some problems as not to consider the periodically changing circumstances caused by construction risks or uncertainties which can affect the cost and time in the project, and to regard collected and accumulated data only as a single value when predicting the results on the progress. Accordingly, it is very difficult to accept the even small range of variability based on the anticipation of EAC. Consequently, the study focuses on the possibility methodology to anticipate time and cost accurately on the way to utilize EVMS(Earned Value Management System), and also suggest the way to perform the right estimation of EAC as considering various risks and uncertainties in construction projects.

• 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.

• Korean Journal of Construction Engineering and Management
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• v.14 no.6
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• pp.14-21
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• 2013

While a detailed cost estimation utilizes the comprehensive quantity information obtained from a complete drawing and specification, an approximate cost estimation heavily relies on the subjective decisions. This phenomenon is because the approximate estimation is usually conducted in early stage of the construction phase where the drawing and specification are not available. This study developed a roadway construction cost estimation system which enables users to estimate the approximated cost of the project in early stage. The system identifies the variation of the construction costs due to the road route change using a cased based reasoning(CBR) method. Overall the system is expected to improves the accuracy and effectiveness of the estimation process, because it would provide users with increased accessability and consistent results in early stage of the project which leaded to the increased work transparency.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method