• International conference on construction engineering and project management
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• 2009.05a
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• pp.1170-1175
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• 2009

When managers estimate exact construction cost at early stage and design phase, they can reduce construction cost in a more efficient way than to predict at construction stage. But, the current of public construction cost estimation and management is concentrated almost after detailed design phase. Therefore, construction cost management in design development phase to generally use approximate estimating is not correct. Also, the existing construction cost used the method that estimated by gross floor area-based cost estimates at design development phase. So, it is difficult to show the specific amount of materials and basis about the estimated cost of the construction. This study derived problems and limits of construction management at design development phase in case of public office building project through review of literature and current survey, and suggested estimating process model process of structural construction cost go improve these matters.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.359-364
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• 1999

Providing the reasonable construction cost at the initial stage of the rural development project, is a kety factor of the each step of project , such as propriety analysis , cost planning , design, and planning the progress of work. The explainable construction cost can be estimated at the early stage using the actual cost data by statistical analysis. In this study, the influence factors are extracted by factor analysis with the actual cost data of rural development project, object cost model is developed by multiple regression analysis, and verify the developed cost model by Monte-Carlo simulation .

• 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.

• 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 Management Science Review
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• v.20 no.2
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• pp.179-196
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• 2003

Function point model is the international standard method to measure the software size which is one of the most important factors to determine the software development cost. Function point model can successfully be applied only when the detailed specification of users' requirements is available. In the domestic public sector, however, the budgeting for software projects is carried out before the requirements of softwares ere specified in detail. Therefore, an efficient function point estimation method is required to apply function point model at the early stage of software development projects. The purpose of this paper is to compare various function point estimation methods and analyse their accuracies in domestic software projects. We consider four methods : NESMA model, ISBSG model, the simplified function point model and the backfiring method. The methods are applied to about one hundred of domestic projects, and their estimation errors are compared. The results can used as a criterion to select an adequate estimation model for function point counts.

• Journal of the Korea Institute of Building Construction
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• v.13 no.1
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• pp.66-74
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• 2013

In the early stages of a construction project, the most important thing is to predict construction costs in a rational way. For this reason, many studies have been performed on the estimation of construction costs for apartment housing and office buildings at early stage using artificial intelligence, statistics, and the like. In this study, cost data held by a provincial Office of Education on elementary schools constructed from 2004 to 2007 were used to compare the multiple regression model with an artificial neural network model. A total of 96 historical data were classified into 76 historical data for constructing models and 20 historical data for comparing the constructed regression model with the artificial neural network model. The results of an analysis of predicted construction costs were that the error rate of the artificial neural network model is lower than that of the multiple regression model.

• Journal of the Korea Institute of Building Construction
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• v.23 no.1
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• pp.103-111
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• 2023

Accurate cost estimation in the early stages of a construction project is critical to the successful execution of the project. In this study, an ANFIS model was presented to predict construction costs in the early stages of a construction project. To increase the usability of the model, open construction cost data was used, and a model using limited information in the early stage of the project was presented. We analyzed existing studies related to ANFIS to identify recent trends, and after reviewing the basic structure of ANFIS, presented an ANFIS model for predicting conceptual construction costs. The variation in prediction performance depending on the type and number of membership functions of the ANFIS model was analyzed, the model with the best performance was presented, and the prediction accuracy of representative machine learning models was compared and analyzed. Through comparing the ANFIS model with other machine learning models, it was found to show equal or better performance, and it is concluded that it can be applied to predicting construction costs in the early stage of a project.

• Korean Journal of Computational Design and Engineering
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• v.15 no.4
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• pp.261-270
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• 2010

These days, architectural projects are becoming larger and more complex. And lots of information occurs through each phases and areas. For these reason, it is emphasized that collaboration with other parts. Therefore we need more effective architectural design process. However, it is difficult to collaborate in early stage with existing design process and it causes unnecessary spending of time and cost because of 2D-based working system. For solving these problem, we should introduce BIM-based Integrated Design Process which makes it possible to collaborate with other parts from early stage. Now the AEC industry in Korea has been trying to introduce BIM, and promoting variety of related business. However, for actual application of this system, it is unfortunately necessary to change various system throughout the construction industry. And this will cause lots of effort and expense. It is essential that scientific analysis and evaluation of efficiency and validity about this investment, because estimation of the investment and accompanying effects will provide reasonable standard of judgment for investment decision. Thus, this research conducted Cost-Benefit Analysis about BIM-based Integrated Design Process compared to existing design process. It is expected that this paper can be used for preliminary data in the future BIM market.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.261-266
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• 2007

In this research, we studied an estimating method in client's sight to estimate the total construction cost which is based on the historical cost data at the early stage of the office buildings as a public phase. It is very difficult to analyze the estimation accurately and logically. When a client estimates a project, he/she has to consider there are many issues at the planning step, according as office buildings become gradually diversified as well as their roles continuously extended. Therefore, those are usually make problems for wasting the budget in accordance with the cost estimation errors. Moreover, many kinds of public construction projects, especially such as school, office, sports complex, and the others, have been invested the private finances defined as BTL(Build Transfer Lease) method that are required to manage the detailed process more strictly from initial planning. In order to make an effective planning, the long-term users amount and the building life cycle at the beginning of project should be considered previously and then it may enable to achieve an appropriate project plan. But actually considering overall variables in a building planning is impossible. Accordingly, suggesting a regression model based on the historical cost data from many similar types of office building to support client's role known as estimating the total cost at the early stage. And then performing the test against the proposed model to research the reasonability as using the historical cost data of Japan office buildings.

• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.81-88
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• 2011

Providers haven't recently had a flexible construction cost estimation system to meet various needs of consumers about public housing. So the subject of this study is to estimate construction cost reasonably in early project stage of public housing and then develop reliable means which is able to support construction cost management and establish a adequate funding investment plan as a provider. In this study, Regression analysis was performed by the case on 20 public apartment complex which were designed from the first half of 2007 to the first half of 2008. A total construction cost of construction, civil engineering, machinery, elevator, land scape, electricity and communication work was used as one sample for increasing explanation and representativeness of the case. In addition, The total construction cost which is devided into design, contract and completion cost was variously analysed for increasing relevance of model and actual utilization. The result of estimation model based on a total construction cost set up completion and design cost showed that error rate is within 2%, which is a excellent result. The estimation model of the construction cost developed by this study is expected to estimate approximate construction cost which is adjacent real construction cost in early stage of the project by using some data.