• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.3
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• pp.49-56
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• 2011

Estimating optimum hardware capacity of an e-learning system is very important process to grasp reasonable size of designing technique architecture and budget during step of ISP(information strategic planning) and development. It hugely influences cost and quality of the whole project. While investment on information system hardware has been continuously increased, there was no certified hardware capacity estimating method in e-learning system development. A guideline for hardware sizing of information systems was established by Telecommunication Technology Association in 2008. However, the guideline is not appropriate for estimating optimum hardware capacity of an e-learning system because it was designed to provide general standards for estimating hardware capacity of various types of projects. The purpose of this paper is to provide a methodology for estimating optimum hardware capacity in e-learning system development. To develop the methodology, this study, first of all, analyzes two e-learning development projects, in which the guideline was applied to estimate optimum hardware capacity. Then, this study finds out several key factors influencing on hardware capacity. Finally, this study suggests a methodology for estimating optimum hardware capacity of an e-learning system, in which weights for the factors are determined through AHP analysis.

• Journal of Construction Engineering and Project Management
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• v.4 no.4
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• pp.9-16
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• 2014

The purpose of this paper is to develop a model for forecasting early design construction cost of building projects using Artificial Neural Network (ANN). Eighty questionnaires distributed among construction organizations were utilized to identify significant parameters for the building project costs. 169 case studies of building projects were collected from the construction industry in Gaza Strip. The case studies were used to develop ANN model. Eleven significant parameters were considered as independent input variables affected on "project cost". The neural network model reasonably succeeded in estimating building projects cost without the need for more detailed drawings. The average percentage error of tested dataset for the adapted model was largely acceptable (less than 6%). Sensitivity analysis showed that the area of typical floor and number of floors are the most influential parameters in building cost.

• Korean Journal of Construction Engineering and Management
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• v.23 no.2
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• pp.54-64
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• 2022

Since the interest in big data is growing exponentially, various types of research and development in the field of big data have been conducted in the construction industry. Among various application areas, cost estimating can be a topic where the use of big data provides positive benefits. In order for firms to make efficient use of big data for estimating tasks, they need to establish a strategy based on the multifaceted analysis of internal and external environments. The objective of the study is to develop and propose a strategy of the use of big data for construction management(CM) firms' cost estimating tasks based on the SWOT analysis. Through the combined efforts of literature review, questionnaire survey, interviews and the SWOT analysis, the study suggests that CM firms need to maintain the current level of the receptive culture for the use of big data and expand incrementally information resources. It also proposes that they need to reinforce the weak areas including big data experts and practice infrastructure for improving the big data-based cost estimating.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.922-925
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• 2008

Many highway projects are under way in Korea. However, owners frequently find that the project cost exceeds the budget and they are unable to identify the underlining reasons. The main purpose of this research is to develop cost models for transportation projects in Korea using the multiple linear regression (MLR). The data consist of 27 completed transportation projects, built from 1991 to 2001, The technique of multiple regression analysis is used to develop the parametric cost estimating model for total budget cost per highway square meter (TBC/$m^2$). Findings of the study indicated that MLR car be applied to highway projects in Korea. There are twf) major contributions of this research. (1) the identification of transportation parameters as a significant cost driver for transportation costs and (2) the successful development of the parametric cost estimating models for transportation projects in Korea.

• Journal of the Society of Disaster Information
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• v.8 no.4
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• pp.328-335
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• 2012

The resource-based estimating based on standard unit price of construction work was estimated by multiplying the price per standard unit of work on the amount of labor, material, equipment use time. However, limitation of the resource-based estimating way does not adequately reflect the actual transactions prices. On the subject of water tunnel excavation as a new attempt to overcome these limitations, this study analyzed productivity by work type into cutter inspection/ exchange, TBM maintenance, TBM inspection/refueling, subsequent installations, tramcar, operating change, a cave-underground reinforcement / rock reinforcement, safety / meetings and analyzed actual cost estimating and the net advance rate based on this analysis result. Actual cost estimating calculation approach presented in this study can be utilized as a useful tool to predict the actual cost estimating in the TBM water tunnels field.

• Current Research on Agriculture and Life Sciences
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• v.26
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• pp.31-43
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• 2008

Introduction of construction cost estimating system is necessary to promote appropriate reflection of construction cost and simplified and efficient amount work. The results of this study are as follows. In the results of considering the basic concept and composition of a construction type estimating system, an example orders are concentrated on an apartment house in the country. The building appurtenant work of extension work is high(1.52) as compared with others. In regression analysis for a construction cost, the models are as follows. In a new construction work, (construction cost)=$12,004.8+4.09{\times}$(building area), and in extension work, (construction cost)=$-121.9+4.50{\times}$(building area). Accordingly, this study wishes to compare and analyzes main contents of original cost method and results cost method, and propose predetermined amount estimation device through existent literature study investigation for accumulation of the construction cost.

• 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.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.3
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• pp.351-361
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• 2009

Many manufacturers define the system of a new product flexibility, and take advantage of previous-product information using the product configuration concept. Product configuration is an approach that defines the system of a new product centered on the product structure by referring to the previous-product information. In this paper, it is established how to apply the concept of a product configuration utilizing previous-ships information in construction cost estimation process systematically and effectively. For this, we define the advanced-construction cost estimation process based on a naval ship product model, and design construction cost estimating model. It is validated that this process and model have the applicability through the case study of the construction cost estimating of the mine-warfare ship.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.383-386
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• 2001

The ability to make good cost overruns predictions is a very important aspect of in major construction project. The probabilistic cost models can provide more reliable than traditional cost models which have been used in korea to prepare Bill of Quantities, if the actual cost data are sufficient enough to analyze the trends of the variables. The paper considers non-deterministic methods in a cost estimate. The method(referred to as the 'Monte Carlo simulation' method) interprets cost data indirectly, to generate a probability distribution for total costs from the deficient elemental experience cost distribution. The objectives of this research is to develop a method to forecast the probabilistic total construction cost and the elemental work cost

• International conference on construction engineering and project management
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• 2013.01a
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• pp.488-493
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• 2013

Accurate initial cost estimates are essential to effective management of construction projects where many decisions are made in the course of project management by referencing the estimates. In practice, the initial estimates are frequently derived from historical actual cost data, for which standard distribution-based techniques are widely applied in the construction industry to account for risk associated with the estimates. This approach assumes the same probability distribution of estimate errors for any selected estimates. This assumption, however, is not always satisfied. In order to account for the probabilistic nature of estimate errors, an alternative method for measuring the risk associated with a selected initial estimate is developed by applying the Bayesian probability approach. An application example include demonstrates how the method is implemented. A hypothesis test is conducted to reveal the robustness of the Bayesian probability model. The method is envisioned to effectively complement cost estimating methods that are currently in use by providing benefits as follows: (1) it effectively accounts for the probabilistic nature of errors in estimates; (2) it is easy to implement by using historical estimates and actual costs that are readily available in most construction companies; and (3) it minimizes subjective judgment by using quantitative data only.