• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.585-588
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• 2007

This study attempts to analyze estimating process and the level of information performing literature review and questionnaire and identify phased influence factors on construction cost using phased information of project and suggests framework of approximate estimation model at the planning and design stage. This paper suggests phased influence factors on construction cost and framework of approximate estimation model for integrated project cost management.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.607-612
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• 2007

Early cost estimation promote efficient budget plan by comparing alternatives and presenting cost information However it is hard to predict accurate cost because of vague cost standard and lack of available information in the early stage. The precious cost model has limitations in the accuracy because they are simple linear model which uses the unit cost per kilometer. This study presents the framework of early cost estimation for road construction projects to overcome the limitation of previous cost model. This study analyzed domestic and foreign cost model and cost data of previous road construction project to present method of cost model framework.

• 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.

• Korean Journal of Construction Engineering and Management
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• v.10 no.4
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• pp.87-100
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• 2009

The quality of early cost estimates is critical to the feasibility analysis and budget allocation decisions for public capital projects. Various researches have been attempted to develop cost prediction models in the early stage of a construction project. However, existing studies are limited on its applicability to actual projects because they focus primarily on a specific phase as well as utilize restricted information while the amount of information collectable differs from one another along with the project stages. This research aims to develop two-staged cost estimation model for the schematic planning and preliminary design process of a construction projects, considering the available information of each phase. In the schematic planning stage where outlined information of a project is only available, the Case-Based Reasoning model is used for easy and rapid elicitation of a project cost based on the extensive database of more than 90 actual highway construction projects. Then, the representing quantity-based model is proposed for the preliminary design stage where more information on the quantities and unit costs are collectable based on the alternative routes and cross-sections of a highway project. Real case studies are used to demonstrate and validate the benefits of the proposed approach. Through the two-stage cost estimation system, users are able to hold a timely prospect to presume the final cost within the budge such that feasibility study as well as budget allocation decisions are made on effectively and competitively.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.445-448
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• 2008

This study attempts to estimate approximate cost on construction of PSC BEAM Bridge using Case-Based Reasoning and suggests approximate estimation model at the planning and design stage. This paper suggests phased influence factors on construction cost and approximate estimation model for integrated project cost management.

• Korean Journal of Construction Engineering and Management
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• v.24 no.5
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• pp.22-34
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• 2023

Predicting accurately the construction cost budget in the early stages of construction projects is crucial to support the client's decision-making and achieve the objectives of the construction project. This holds true for public construction projects as well. However, the current methods for predicting construction cost budgets in the early stages of public construction projects are not sophisticated enough in terms of accuracy and reliability, indicating a need for improvement. The objective of this study is to develop a construction cost budget prediction model that can be utilized in the early stages of public building projects using an artificial neural network (ANN). In this study, an artificial neural network model was developed using the SPSS Statistics program and the data provided by the Public Procurement Service. The level of construction cost budget prediction was analyzed, and the accuracy of the model was validated through additional testing. The validation results demonstrated that the developed artificial neural network model exhibited an error range for estimates that can be utilized in the early stages of projects, indicating the potential to predict construction cost budgets more accurately by incorporating various project conditions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5D
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• pp.677-684
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• 2008

The paper provides an approximate cost estimating model that can be used for tunnel. Based on the previous study analyzed critical factors that have impact on tunnel construction cost, this paper establishes a cost variance index table that reflects the cost impacts due to the change of the critical cost factors. An estimating procedure is described utilizing the index table. For the verification of the suggested model, the comparison of the estimated construction cost with real project cost is performed. The estimated results range from 95%~111% of the real project costs. As an approximate tunnel cost estimating model, the model can be utilized to quickly estimate tunnel construction costs based on the conceptual information at the planning stage and to efficiently make a decision on design alternatives.

• Korean Journal of Construction Engineering and Management
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• v.19 no.5
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• pp.81-89
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• 2018

The purpose of this study is to assess the risk and predict the contingency for modular plant construction projects. Considering the work characteristics of the modular plant, The adapted research method is that suggest models for assessment impact of risk and predict the contingency considering risk. Based on the proposed models, It is selected one modular plant construction project and assessment impact of risk factors and predicted the contingency. The results of this study are as follows: Assessment the probability of occurrence of risk factors and intensity of impact, and extract 15 important risk factors. These are classified as Engineering, Procurement, Fabrication, Transportation, Construction phases to consider the work characteristics of the modular plant. The predicted contingency is that 6.739%(Engineering 2.850%, Procurement 6.225%, Fabrication 6.211%, Transportation 4.165%, Construction 8.168%) to prepare the basic business expense. The model is used as a way to derive quantitative results in the decision-making process for risk management in construction projects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3D
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• pp.373-379
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• 2009

Cost estimation in the early phase enables government to plan public budgeting more efficiently by providing information about construction cost. However, cost estimation in the early phase is difficult to predict because only a little information can be utilized. The cost estimation method now being used by the government is calculated by length of the road multiplied by unit cost per length and shows high error rate because it cannot reflect the unique characteristics of each project. As the project is being proceeded, level of available information also changed. So, reflecting available information of a project is important. This paper divided early phase into two parts : planning phase and early design phase, and developed cost estimation model considering level of available information of each phase. Total 143 cases are utilized to find influencing variables and develop cost estimation model and model validation is done by adopting required accuracy level. This cost estimation model reflecting level of available information can be applied to public budgeting, feasibility test, and comparison between routes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.747-753
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• 2015

요즘 우리의 생활 속에서 차세대 신기술로 주목할 만한 것이 바로 "빅 데이터" 이다. 하지만 빅 데이터는 아직 구체적인 개념이 모호한 상태이다. 빅 데이터란, 기존 데이터베이스 관리도구로서 데이터를 수집, 저장, 관리, 분석할 수 있는 역량을 넘어서는 대량의 정형 또는 비정형 데이터 집합 및 이러한 데이터로부터 가치를 추출하고 결과를 분석하는 기술을 의미한다. 이러한 분석된 데이터들은 여러 방면으로 활용이 가능하다. 이를 통해 기업에서는 비즈니스적인 활용이 가능하며 예측과 분석을 통해 사업전망을 내다볼 수도 있다. 따라서 본 논문에서는 비즈니스 모델 혁신을 위해 빅 데이터 기반 예측분석이 왜 필요한 지에 대해 논의하고 기업들이 혁신을 촉진하기 위해 사업전략 목표에 예측모델들을 활용하는 운영 모델을 제시하고자 한다.