• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.137-142
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• 2006

Cost and duration is important factors which directly affect profit therefore must be forecasted correctly to accomplish success of projects. So construction company uses EVMS(Earned Value Management System) to forecast final cost and duration. But previous forecasting model has low accuracy because of its linear forecasting method and can't reflect characteristic of company and project and changes as each progress. This paper presents cost and duration forecasting model using the slope prediction of cost and duration as each progress to reflect the various characteristics of construction industry. EVMS data of 23 road construction projects was used to make up regression analysis equation of slope forecasting model.

• Journal of the Korea Institute of Building Construction
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• v.7 no.1 s.23
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• pp.63-70
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• 2007

The aims of this study are to draw the project risk factors by grasping the relation especially between the construction preparation cost calculation and the project risk factors in the project's bidding stage, and to draw the cost estimate based on the risk when the orderer or the constructer performs the project and the main factors in calculating the most suitable construction cost by clarifying the understanding degree of the influence between the risk factors and the construction cost. In addition, this study can give a help to the proper decision -making through the prediction of the construction preparation cost, and this study is expected to give the basic data in developing the assessment tool for the most suitable construction cost of the project.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.05a
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• pp.162-163
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• 2014

Operation and maintenance stage consists the largest portion of project life cycle cost. Appropriate management and analysis of such stages have massive effect on the total project cost. The effective prediction of optimized repair period is one of main factors in ㅌ management. However, it has been analyzed that the prediction of appropriate repair period revealed limitations in reliability. Therefore, this study suggests a methodology of repair period prediction by dividing finished projects into similar groups with same properties to be compared with the target project using quantitative variables.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.510-515
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• 2011

Urban renewal projects, in the form of mega-projects, are being actively implemented both nationally and internationally to revitalize inactive cities. These programs, however, are difficult to manage efficiently due to their need for a large budget over a long period of time and due to conflicts with stockholders. Moreover, existing cost and duration management systems are structured with emphasis on the design and construction stage of unit projects, thus limiting their application to long-term mega-projects that are integrated with various facilities. To solve these problems, this study developed a web-based system that can collectively manage the cost and duration of mega-projects at a program level. The unit modules included in the system--CBS organization, construction cost and duration prediction, and total cost and duration prediction--can support decision-making at the early stage of the program. Furthermore, the modules, which include contract management, execution management, change management, and program progress management, support the program operations for its successful accomplishment. The web-based cost and duration management system developed in this study is expected to be used as a valuable tool that supports the successful accomplishment of mega-projects through their efficient management throughout their life cycle.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.111-116
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• 2006

The objective of this research is to develop an assesment system for BTL Project. A new method for the prediction of construction and maintenance cost in the educational facilities has been considered and under development by the authors. This paper explains the current BTL assesment method used by most local district office of education and lists its potential problems. Main conceptual modules in the new Assesment System are shown in this paper. Also, viable results of each module are discussed in this paper.

• Korean Journal of Construction Engineering and Management
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• v.10 no.3
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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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.419-422
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• 2002

The features of modem construction industry can be summarized as specialization, complexity, and large-scale. Therefore, increasing uncertainty of construction project can not be effectively dealt with traditional method used for construction cost management. Cost overrun affects on successful execution of managing construction project in a negative way. Therefore, accurate estimation is a priori for effective cost management. First, this work analyzes the previous cost estimation model for the effective cost management. Then, a standard structure required for developing the cost estimation model for site development was presented. In addition, the cost estimation model which can be used in planning and design phases was introduced by analyzing real site development projects.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.232-233
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• 2021

As construction projects become larger and more complex in the construction environment, and as the Building Information Model(BIM) is technically introduced, the demand for construction costs in units of space is increasing. Cost estimating of spacial element can reduce the error in cost prediction method based on cost of work type and to utilize the construction cost data for each space in the design phase. The purpose of this study is to extract spatial statements by utilizing spacial information of quantitative statements based on items that are common elements of the Quantity Take-Off and Bill of Quantity.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.913-916
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• 2005

This paper presents the development of Artificial Neural Network models for forecasting the cost and contract duration of school reconstruction projects to assist the planners' decision-making in the early stage of the projects. 132 schools reconstruction projects in central Taiwan, which received the most serious damage from the Chi-Chi Earthquake, were collected. The developed Artificial Neural Network prediction models demonstrate good prediction abilities with average error rates under 10% for school reconstruction projects. The analytical results indicate that the Artificial Neural Network model with back-propagation learning is a feasible method to produce accurate prediction results to assist planners' decision-making process.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1299-1306
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• 2014

Recently, there are many roundabouts installation works which are ordered to provide convenient transportation to road users as well as to eliminate traffic accidents and traffic delays. This study propose an approximate construction cost estimation model for early stages of roundabout construction. The model is designed considering the conditions of the early stage roundabout construction sites in Jeju. The regression equation of approximate construction cost was derived through regression analysis of 25 design data of roundabout construction in Jeju, and it was analyzed to have a high prediction accuracy. Finally, results verifies high prediction accuracy of the derived regression equation. Difference between the estimation cost and the design cost was only 2.3%, 3.7%, and 5.8% that verifies the high accuracy of the proposed approximate construction cost estimation model.