• Korean Journal of Construction Engineering and Management
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• v.15 no.4
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• pp.68-76
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• 2014

The accurate estimation of construction cost is important to a successful development in construction projects. In previous studies, the construction cost are estimated by statistical methods. Among the statistical methods, support vector regression (SVR) has attracted a lot of attentions because of the generalization ability in the field of cost estimation. However, despite the simplicity of the parameter to be adjusted, it is not easy to find optimal parameters. Therefore, to build an effective SVR model, SVR's parameters must be set properly without additional data handling loads. So this study proposes a novel approach, known as genetic algorithm (GA), which searches SVR's optimal parameters, then adopt the parameters to the SVR model for estimating cost in the early stage of apartment housing projects. The aim of this study is to propose a GA-SVR model and examine the feasibility in cost estimation by comparing with multiple regression analysis (MRA). The experimental results demonstrate the estimating performance based on the percentage of estimations within 25% and find it can effectively do the accurate estimation without through the trial and error process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.829-837
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• 2011

Construction cost estimation in planning phase which calculates the cost for performing construction tasks is used for various ways. Meanwhile, in the case of road construction, the existing cost estimating method in early phase based on numerical mean value of the past is not accurate to be used. This paper propose neural network model for estimating road construction cost in planning phase to solve the limit of current cost estimating method. The model was designed using past road construction bidding records, and variables of model were optimized through trial and error. The estimation result of the model was compared with regression analysis and government's standard and it was verified that the model is better in accuracy. It is expected that the proposed model will be used for road cost estimation in planning phase.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.66-76
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• 2008

Plant project is a complex project that consists of civil engineering, building, mechanical and electronic works. The schedule management is one of important factors in plant project because the construction duration of the project is very short comparing with the other construction projects. Specially, 4D CAD system needs to visualize construction schedule information in those complex projects. This study suggests methodologies for improving 4D CAD functions by considering those project characteristics. To develop a plant 4D CAD system, this study includes to develop new functions by analyzing actual schedule information from the plant construction sites.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1296-1301
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• 2005

하천자연도 평가는 하천이용과 보전, 복원계획에 대한 적합성의 근거를 파악하고 이에 가치를 부여하기 위해 주로 평가가 이루어진다. 최근 많은 하천들이 자연형 공법을 적용하여 정비되고 있지만 하천 정비에 따른 실효성 검토가 제대로 이루어지지 않고 있다. 자연형 하천으로 정비된 하천의 실효성을 검토하는 하나의 방법으로 지속적인 모니터링을 통해 하천생태계의 구조와 기능을 파악하고 수집된 자료를 분석하여 공사전과 공사후 하천자연도를 평가할 필요가 있다. 본 연구에서는 GIS를 이용하여 공사전과 공사후의 하천자연도 평가를 수행하였다. 평가항목은 종단면, 횡단면, 하상구조, 하천주변, 하천수질, 식생, 어류, 조류 등 8개 부문 29개 항목을 반영하였고 공사전과 후의 자연도 평가를 비교하기 위해 공사전 모니터링을 통해 얻은 자료를 바탕으로 부문별 평가항목 7개 부문에 17항목을 평가하였다. 평가의 척도는 정량적 지수로서 $1\~5$의 점수로 하였고 하천자연도의 표현은 5등급 체계로 구분하고 가중치는 부문별로 동일하게 하였다. 본 연구의 결과는 공사전 평가지수 3.3으로 하천자연도 III등급이었으나 공사후에는 평가지수 2.7로 II등급을 나타내었다.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.523-526
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• 2002

In the bearing wall systems, a form work has a lot of room that saves cost because it takes a substantial proportion of construction cost. Therefore the systemic and efficient methods are required in the form work. This study focuses on methods that enhance the quality and the productivity of form work and presents the kicker form as an alternative plan to simplify the form work through being modular and automatical it. Work sampling method is used for productivity measurement. It is expected that it will reduce the work process and improve the Qualify and the podructivity of construction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.347-353
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• 2008

Generally speaking, it is important to know the activities itself exactly and to control the activities correctly so as to assure timely progress and the quality of any project. In order to progress smoothly in accordance with construction schedule, it is important to systematize the preliminary arrangements necessary for each process and then manage them. In this study, in order to progress smoothly the quality and schedule management of the construction, we can be made systematically pre-works in accordance with construction schedule by the civil construction items of the apartment house construction. we suggested pre-construction control item by the workers through experiential method of construction engineers in accordance with network schedule.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.366-372
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• 2012

In most of construction work, especially mat foundation construction, it is very important that accidents be prevented at early aged construction stage. To reduce the risk of accidents, it is necessary to choose the curing method to provide instructions for safety forming work by proper curing of concrete after placing. Therefore, this paper has proposed a designation algorithm of curing method for representing curing type and period by analyzing the transient hydration heat solution, focusing on mat foundation construction. This has been implemented, moreover, using an object oriented programming language to develop structural analysis system taking account crack index. In addition, we present in this paper a safety curing management system developed to assess risk during forming work.

• Journal of the Korea Institute of Building Construction
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• v.9 no.5
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• pp.135-144
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• 2009

The primary focus of this study has been directed towards assessing the potential impact of construction method improvement on a reduction in project cost. A total of 90 actual application cases were collected from a public organization and private construction firms, and 32 cases were used in analysis by adopting a synthetic approach. The level of cost reduction was measured in terms of material and labor cost by comparing the existing method and the improved method. An analysis of the results indicates that project cost can be reduced by up to 5.26 percent compared to a normal project by adopting a synthetic approach. Additional benefits include the assurance of uniform quality, savings in terms of labor and/or materials, and improved productivity. The potential of the applicability of this approach to other types of buildings and the implications of research findings were discussed in detail.

• Journal of the Korea Institute of Building Construction
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• v.11 no.3
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• pp.319-325
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• 2011

During a construction project, construction managers must be provided with material information to help them to make decisions more efficiently without delaying the delivery of material. Construction work can be smoothly performed with the proper material supply. Construction duration depends on several material-related decisions, including the order, delivery, and allocation of material to the correct work location. Hence, it is worthwhile to introduce data warehouse techniques that generate subject-oriented and integrated data to construction material management. The data warehouse for construction material management can perform multidimensional analysis and then define KPIs (Key Performance Index) in order to provide construction managers with construction material information such as lead time, material delivery rate, material installation rate and so on. This research proposes a method of effectively facilitating large amounts of data in the operating systems during the construction management process. In other words, the proposed method can supply structured and multi-perspective material-related information using data warehouse techniques.

• Journal of the Korea Institute of Building Construction
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• v.22 no.3
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• pp.317-326
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• 2022

With the development of various technologies in the area of artificial intelligence, a number of studies to application of artificial intelligence technology in the construction field are underway. Diverse technologies have been applied to the task of predicting construction costs, and construction cost prediction technologies applying artificial intelligence technologies have recently been developed. However, it is difficult to secure the vast amount of construction cost data required for machine learning, which has not yet been practically used. In this study, to predict the construction cost, the latest artificial neural network(ANN) method is used to propose a method to improve the construction cost prediction performance. In particular, to improve predictive performance, a log conversion method of target variables and a feature scaling method to eliminate the difference in the relative influence of each column data are applied, and their performance in predicting construction cost is compared and analyzed.