• 교육녹색환경연구
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• 제10권1호
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• pp.10-25
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• 2011

Area Offices of Education in Korea assign and execute government budget based on the evaluation of school buildings' safety rating and degree of their deterioration. However, it is never easy to estimate the most appropriate investment amount for old buildings under consideration of their service lives and residual values together. A model of estimating optimum investment cost for obsolete school building is developed taking its life cycle cost into account. The model is also applied to six old buildings in five different schools and found that some of the facilities hardly needed further investment and were better to be rebuilt. The study results will be a great beneficial for officers to make right decision on maintaining obsolete school buildings and to maximize tax payers' money.

• 한국시스템다이내믹스연구
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• 제8권2호
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• pp.253-273
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• 2007

To measure the effect of school zone on housing cost, Linear Regression Model is widely used, and school zone is known as a key determinant of housing cost in Korea. However, when the Hierarchical Linear Model (HLM) is applied with the same data, school effect on housing cost becomes statistically non-significant. It is because HLM effectively separates the effect of individual housing's attributes from the group effect. In sum, the housing cost of Kangnam, where good public schools are located, is apparently is higher than that of Kangbuk. However, the school effect on housing cost (Level 2) becomes non-significant when individual housing's attributes (Level 1) are controlled with HLM.

• 경영과학
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• 제23권2호
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.445-448
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• 2008

국내 도로건설사업에 있어서 개략공사비 산정 기준은 건설교통부 및 기획예산처, 한국도로공사 등에서 제시하는 평균 건설단가를 기준으로 활용하고 있다. 이때 도로의 등급, 구조물 추간의 구성 비율 등에 따라 공사비를 도정하고 있으나 다양한 공사 특성을 반영하고, 지속적인 공사비 갱신의 기준 등에 한계를 가지고 있다. 대규모 재원이 투입되는 건설공사의 공사비를 합리적인 방법으로 적정하게 예측하는 것은 사업비 관리 측면에서 필수적인 요소는 기술이라 할 수 있다. 본 연구에서는 기획단계에서 가용한 정보를 활용하여 공사비를 예측할 수 있는 사에 기반추론 PSC BEAM교의 개략공사비 산정모델을 개발하였다. 제시된 공사비 예측모델을 검증하기 위하여 표본교량을 대상으로 공사비를 추정한 결과 $-11.92%{\sim}3.20%$의 추정편차를 나타내었으며, 기존 개략공사비 산정 기준에 비해 신뢰도가 향상되었다.

• 한국농공학회지
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• 제16권1호
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• pp.3302-3318
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• 1974

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.377-377
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• 2000

Current software cost estimation models, such as the 1951 COCOMO, its 1987 Ada COCOMO update, is composed of nonlinear models, such as product attributes, computer attributes, personnel attributes, project attributes, effort-multiplier cost drivers, and have been experiencing increasing difficulties in estimating the costs of software developed to new lift cycle processes and capabilities. The COCOMO II is developed fur new forms against the current software cost estimation models. This paper provides a case-based analysis result of the cost driver in the software cost models, such as COCOMO and COCOMO 2.0 by fuzzy and neural network.

• 한국국방경영분석학회지
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• 제36권1호
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• pp.29-38
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• 2010

In Korea weapon system acquisition processes, it's required a cost estimation report obtained from a commercial cost model. The PRICE model is generally used as a cost estimation model in Korea. However, the model uses American historical R&D data and it's output cost component is different from our cost component of defense accounting system. Also, we found that estimating results show about 10% of difference when we comparing with actual costs in 44 finished weapon acquisition projects. There are some limitations in calibration to increase an accuracy of the PRICE model because it's difficult obtain good real input data, detailed cost and technical data in low level WBS. So, only 8% of the defense R&D projects are calibrated and validation of calibration results is more difficult. Therefore, we studied the standard calibration process and performed the calibration about the MCPLXS/E parameters of the PRICE model based on actual cost data. In order to obtain a good calculation result, we collected the actual material costs from the defense industry companies. Our results can be used for an reference in similar weapon system R&D and production cost estimation cases.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2008년도 정기학술발표대회 논문집
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• pp.197-201
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• 2008

국내 도로건설사업은 평균 단가 기준으로 개략공사비를 산정한다. 도로의 기초자료를 갱신함으로써 평균 단가를 수정하고 있으나 공사 특성을 전부 반영하기에는 미흡한 실정이다. 설계 진행단계에서 설계 대안을 평가하는데 활용할 수 있는 공사비 예측모델의 필요성이 제기되는 가운데 대표공정을 통해 표준물량을 산출하고 개략공사비 산정모델개발을 통해 실질적인 공사비 예측이 가능한 모델을 개발하고자 한다. 본 연구에서는 Prestressed Concrete Box Girder Bridge의 상부공사를 중심으로 연구를 수행하며 $2000{\sim}2007$년 사이에 수행되었던 구조물공 41건에 대한 기초자료를 수집하고 토목공사 수량산출기준에 의한 내역서를 기반으로 Grouping을 실시하여 대표적 특수교량인 ILM(Incremental Launching Method), MSS(Movable Scaffolding System), FSM(Full Staging Method), 그리고 FCM(Free Cantilever Method)등 교량 형식별로 총공사비에서 공사비 비중 및 해당 공종에서의 중요도가 높은 항목을 중심으로 설계 초기단계에서 가용한 정보 수준을 고려하여 대표공종 선정한다. 교량 형식별 선정된 대표공종을 살펴보면 P.S.C 강재설치 및 긴장작업/P.S.C BOX/자재대 및 자재운반비/철근가공 및 조립/증기양생/콘크리트 타설/거푸집/교면 방수/동바리 등 교량형식별 특수성을 제외하면 대표공종들이 순공사비에서 차지하는 비중이 비슷함을 알 수 있다. 공종들이 총공사비에서 차지하는 비율은 ILM(99.47%)/ MSS(99.22%)/ FSM(98.18%)/ FCM(98.12%)로 나타났다.

• 한국건축시공학회지
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• 제11권1호
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• 한국건설관리학회논문집
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• 제10권3호
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• pp.139-147
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• 2009

Accurate construction cost estimation in the initial stage of building project plays a key role for project success and for mitigation of disputes. Total construction cost(TCC) estimation of apartment projects in Vietnam has become more important because those projects increasingly rise in quantity with the urbanization and population growth. This paper presents the application of artificial neural networks(ANNs) in estimating TCC of apartment projects. Ninety-one questionnaires were collected to identify input variables. Fourteen data sets of completed apartment projects were obtained and processed for training and generalizing the neural network(NN). MATLAB software was used to train the NN. A program was constructed using Visual C++ in order to apply the neural network to realistic projects. The results suggest that this model is reasonable in predicting TCCs for apartment projects and reinforce the reliability of using neural networks to cost models. Although the proposed model is not validated in a rigorous way, the ANN-based model may be useful for both practitioners and researchers. It facilitates systematic predictions in early phases of construction projects. Practitioners are more proactive in estimating construction costs and making consistent decisions in initial phases of apartment projects. Researchers should benefit from exploring insights into its implementation in the real world. The findings are useful not only to researchers and practitioners in the Vietnam Construction Industry(VCI) but also to participants in other developing countries in South East Asia. Since Korea has emerged as the first largest foreign investor in Vietnam, the results of this study may be also useful to participants in Korea.