• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.1-14
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• 2013

The world largest land reclamation project in the name of Saemangeum(Ariul) from 1991 to the present has been implementing in a part of the west coast of Korea. In the Saemangeum reclamation project, the large-scale project cost is used for the landfill reclamation. A number of landfill reclamation methods have been studied in order to reduce the large-scale cost of the Saemangeum project under construction. There are many studies related to the on-site real-time monitoring with mobile systems for operating a wide range of landfill. In order to apply the work method for efficient cost-savings in the landfill operations to the Samangeum project, this paper develops a mobile management system that is composed of a mobile interface module, a data server module for data transmission and storage, and an analysis server module to analyze the input data and derive the results. The mobile system is designed by analysing user's and system requirements, functional interactions, and data flow using unified modeling language(UML). The user interface is developed for the on-site real-time monitoring through the status and related attributes of land reclamation by using the digital maps of the Samangeum coverage via mobile devices. Finally, a mobile management system would be developed that can provide a 3D GIS service based on the Dry Internal Project Site Digging Reclamation Method(DIPSDRM).

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.23-38
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• 2019

The National Land Census Project aims to survey the national land regularly to resolve the land category disagreement and reflect the actual land use. The objective of this study is to investigate whether not only the National Land Census Project but also related land and housing surveys bring about the improvement of social welfare in light of the invested budget, and to measure the project feasibility. The potential benefit after the National Land Census Project is not traded in the market. To determine the economic value of this potential benefit, the Contingent Valuation Method was used. This study utilized the single-bounded and double-bounded dichotomous choice models simultaneously to estimate the project feasibility of the cadastral system improvement. According to this study, cost-benefit ratio of the project was estimated larger than 1, which means that social benefits are larger than social costs.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• Korean Journal of Construction Engineering and Management
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• v.8 no.4
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• pp.155-166
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• 2007

The purpose of this research is to develop a conceptual model and prototype that establishes a new approach for building cost estimating in the schematic design phage. This research use the method that analyzes quantity and unit price separately to enhance schematic cost estimating through conducting literature review andi analyzing existing schematic cost estimating methods. In addition, this study proposes tile concept of cost breakdown structure including two more classifications: building element and floor compared to existing one only classified by trade. Thus, a Quantity Based Active Schematic cost Estimating(Q-BASE) model is developed founded on those two concepts. By applying proposed schematic cost estimating model, historical structure cost of residential complex building project is analyzed, and then, based on this analysis, prototype is implemented.

• Korean Journal of Construction Engineering and Management
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• v.13 no.4
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• pp.152-163
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• 2012

At the conceptual phase of a construction project, estimated construction cost is very important as it significantly influences the owner's decision-making. Accurate cost estimating, in the early stage of a public construction project, serves as a critical factor because initial decision-making effects the final cost of a construction project. However in the cases of Korean public apartment projects, excluding a few of the public owners, there is a problem in properly estimating construction cost due to the lack of construction cost estimating system. Thus, this research developed a public apartment cost estimating system using case-based reasoning that was suggested by a previous research with 66 cases of Korean public apartment projects. Based on the system experiments involving 19 public officers and 10 cases of Korean public apartment projects, the effectiveness of the system in terms of estimation accuracy and user-friendly was confirmed. As a result, the developed system has an error range of 1.47% to 13.74% and mean of 6.15%. In addition, the system was evaluated that it could greatly improve the current estimation task of public officers. Consequently, the results of this research can be used as a foundation for a technological advance in estimating construction cost and improving the accuracy and consistency of construction cost estimation.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.42-52
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• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.

• 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.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.698-699
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• 2015

For last three years, our research team have conducted the project named "Development of construction project management technology based on BIM/GIS platform. "We developed construction cost estimation system as well as 3D modeling engine at the first two year and established a web-system which could estimate the benefits of the project and further analyze the economic and financial feasibility of the project. This paper mainly focused on the functions and specifications of web-system. The system was composed of two modules: economic feasibility estimation module and financial feasibility estimation module. While the economic feasibility estimation module determines economic feasibility of the project based on traffic demand forecasting from the public's perspective, the financial feasibility estimation module determine financial viability of the project using toll fee of the road from private entity's perspective. Compared with traditional feasibility study, the proposed system provide users with better flexibility which can make users easily to validate the project upon the change of project environments. The system was also verified with an already accomplished project. The verification showed that proposed system could provide satisfactory accurate results with reduced time and resources.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.335-339
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• 2011

The unique characteristics of the construction industry - such as the fragmentation of its processes, varied scope of works and diversity of its participants - are contributory factors to poor project performance. Several issues are unresolved due to the lack of a comprehensive technique to measure project outcomes including: inefficient decision making, insufficient communication, uncertain site conditions, a continuously changing environment, inharmonious working relationships, mismatched objectives within the project team and a blame culture. One approach to overcoming these problems appears to be to measure performance by gauging contractor satisfaction (Co-S) levels, but this has not been widely investigated as yet. Additionally, the key Co-S dimensions at the project level are still not fully identified. This paper concerns a study of satisfaction dimensions, primarily by a postal questionnaire survey of construction contractors registered by the Malaysian Construction Industry Development Board (CIDB). Eight satisfaction dimensions are identified that are significantly and substantially relate to these contractors - comprising: project cost performance, schedule performance, product performance, design satisfaction, site safety, project profitability, business performance and relationships between participants. -Each of these dimensions is accorded different priority levels of satisfaction by different contractors. The output of this study will be useful in raising the awareness and understanding of project teams regarding contractors' needs, mutual objectives and open communication to help to deliver a successful project.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.324-329
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• 2011

Significant decisions are made by the project team during the early planning phase of capital facility project developments. The preproject planning phase begins after a decision is made to proceed with a project concept and continues until the detail design stage. Many of the industry practitioners and researchers have recognized the importance of preproject planning and that inadequate early planning is one of the key factors affecting project success. Nevertheless, the preproject planning practices vary significantly for the construction industry in Taiwan and the quality of preproject planning relies heavily on individual project team's experience. This research sets out to benchmark the preproject planning practice for the building construction industry in Taiwan. From late 2007 to early 2010, the researchers collected information from a total of 92 building construction projects using questionnaire survey. The analysis results show that the surveyed projects with better preproject planning have better cost and schedule performances on average. It is recommended that project team spend more efforts in the preproject planning stage to have a better chance of achieving project success.