• 한국건축시공학회지
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• 제15권3호
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• pp.307-316
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• 2015

공공건축물공사의 실적공사비제도에서 공사규모에 대한 건축공사비 차이가 크게 나타나므로, 산정방식에서 많은 문제점으로 제기된다. 이에 공사규모에 따라서 선별적, 차등적으로 적용할 예측모형의 개발이 필요하다. 이에 본 연구는 조달청에서 2011~2012년에 발주한 이미 준공된 42개 현장의 실적자료에서 공사규모 $5,000m^2{\sim}20,000m^2$으로 선정하여, 회귀분석을 통해서 추정된 모형을 도출하였다. 이를 근거로 신규공사에 적용하여 검증함으로써 합리적인 건축공사비 예측모형을 제시하였다.

• 대한토목학회논문집
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• 제28권5D호
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• pp.665-675
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• 2008

본 연구는 터널공사를 대상으로 사업 초기단계에서 터널공사의 설계 대안에 대한 공사비를 신속히 추정하고, 사업이 진행되면서 상황변화에 따른 사업비 측면에서의 영향을 파악할 수 있도록 함으로써, 적정한 의사결정을 지원하기 위한 개략적 터널공사비 추정모델 제시를 목적으로 한다. 이를 위해 터널공사의 수행에 있어 공사비에 영향을 미치는 요인을 분석하고, 공사비 영향요인별 공사비 변화의 정도를 분석하였다. 공사비 영향요인은 천공방식, 굴착방법, 기폭장치, 적재장비 용량, 버력의 단위중량 및 토량환산계수, 터널 연장을 포함하는 7개의 요인을 대상으로 하여 각 영향요인의 변화에 따른 공사비 변동 크기를 분석하였다. 분석결과는 기획단계에서 사업의 기본적인 조건을 바탕으로 사업비를 추정하고, 설계 및 시공단계에서 설계 대안에 대한 공사비의 영향을 효율적으로 평가하는데 필요한 공사비 추정모델의 구축을 위한 기초정보를 제공할 것으로 기대된다.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.182-186
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• 2011

Early cost estimates are important to decision-making for a construction project. Moreover, the possibility of reducing the project cost is getting less as the project is progressed. Case-based reasoning (CBR), which can be viewed as an effective method for early cost estimating, is widely utilized recently. Early cost estimates using CBR have advantages over the traditional ones as they produce reasonable outputs and self-studying is possible by simply adding new cases. Case-based reasoning is composed of a cycle of retrieve, reuse, revise, and retain process. However, in the majority of research cases, they are focused on how to retrieve the similar cases, instead of revising the cases which is expected to increase accuracy results of cost estimation. This research suggests a method of revising retrieved similar cases in a GA-CBR cost model which is widely studied and utilized for early cost estimating recently. To validate the proposed method, case study is conducted based on Korean public apartment projects.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.176-181
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• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.256-261
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• 2011

Labor productivity is a significant factor related to control time, cost, and quality. Many researchers have developed models to define method of measuring the relationship between productivity and various constraints such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only contains the average productivity data of the construction industry, and it is difficult to predict the time and cost of any particular project; hence, there are some errors in estimating duration and cost for individual activity and project. To address these issues, this research collects data, measures productivity, and develops time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites and it is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1242-1247
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• 2009

The sudden changes in the construction market and the progressively intensifying price wars have amplified the importance of the construction cost estimation in the initial and planning phases of construction projects. However the methodologies and process of estimating construction cost in the planning and design phase are not standardized in the domestic market, in contrast to the markets of more developed countries. Therefore this paper proposes a new approximate estimation model to be used from the initial stages of construction projects. This methodology that extracts, modifies and synthesizes comparable elements of previous cases. This will introduce the foundation for the implementation of systems with improved usability and applicability.

• Journal of Construction Engineering and Project Management
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• 제4권4호
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• pp.9-16
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• 2014

The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

• 도시과학
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• 제6권2호
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• pp.35-47
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• 2017

Tax evasion is increasing, but efficiency of tax administration is evaluated as improving. This is because the taxation cost, which is a measure to judge the efficiency of the tax administration, does not consider the tax evasion effect at all. This method of estimating the cost of taxation is a dispute that neglects the role of taxation authorities in tax evasion. The existing study focuses on the development of a tax evasion model focused on maximizing the utility through the tax evasion of the taxpayer as the tax evasion approaches the individual 's deviant problem. However, this has the aspect of making the role of the tax authorities in tax evasion negative. This study empirically derived the optimal size of tax administration in Korea by using tax collection cost and tax cooperation cost. Also, it is meaningful to consider the role of the taxation authorities in tax evasion and to derive the optimal taxation cost model by estimating the decrease in tax evasion due to the taxation expenditure of the tax authorities. In order to derive the optimal size of tax administration in Korea, taxation cost and tax cooperation cost are derived by classifying tax officials. The optimal taxation cost model was derived by estimating the taxation expenditure related to tax evasion. This study is meaningful to make it possible to emphasize the role of tax authorities in studying future tax evasion by studying the effect of taxation expenditure on tax evasion.

• 대한토목학회논문집
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• 제31권6D호
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• pp.829-837
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• 2011

공사비 견적이란 건설공사를 수행하는데 소요되는 공사비를 산정하는 것으로, 공사 기획단계에서 사용하는 개략견적은 다양한 목적으로 사용된다. 한편, 도로공사의 경우, 현행 사용되는 개략견적방법은 과거의 실적자료를 산술평균하여 단위 km당 공사비를 제시한 것으로 실제 개략공사비로 활용하기에는 어려움이 있다. 본 연구에서는 기획단계의 도로공사견적 산정방식에 대한 한계를 해결하기 위하여, 인공신경망을 적용한 개략공사비 모델을 제시하는 것을 목적으로 한다. 도로건설 공사입찰을 위한 기본설계도면 작성 이후 공사비를 결정하는 변수를 포함한 과거 실적 자료를 바탕으로 인공신경망을 적용하여 기획단계에서 공사비 예측이 가능한 도로 공사비를 개략견적 하는 모델을 설계하였으며, 시행착오방식을 이용하여 모델의 변수들을 최적화하였다. 또한 최적화된 모델을 통해 나온 결과를 회귀분석을 적용한 결과와 비교하여 정확도가 뛰어남을 검증하였다. 제안된 인공신경망모델은 차후 도로건설공사의 개략공사비 산정을 위한 활용될 것으로 기대된다.

• 한국군사과학기술학회지
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• 제15권5호
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• pp.565-576
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• 2012

Cost estimates are necessary for government acquisition program to support decisions about funding, to develop annual budget requests and to validate resource requirements at key decision points. Many researches have been done about cost estimating technique recently. Parametric cost estimating models based on CERs(Cost Estimating Relationships) have been mainly used using regression method with historical data. However, there are many restrictions in developing Korean version CERs because the number of data points are too small. Specially, data collection and data management system are unstable in Korean defense environment, when developing CERs. In this research, we analyzed the historical data, and found some cost drivers in guided weapon system area. We developed the Acquisition Unit Cost CER using the regression to remove multicollinearity in the historical data. So we could overcome the restriction of the insufficient sample number. This research as a first attempt is meaningful in terms of obtaining our own Acquisition Unit Cost CER using historical cost and physical characteristic in Korean development environment.