• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.44-54
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• 2018

In the construction project, the design field has a crucial effect on the success or failure of the final product, and it is becoming more important as a core area of national industrial development because it creates high value added by technology. In addition, since the design work is carried out based on professional technical personnel, in order to secure the quality and competitiveness of the design, it is necessary to continuously input the excellent manpower and develop the technology, and above all, the appropriate design cost must be ensured. However, as a result of reviewing the current status of the design cost criterion in Korea, problems such as mixed cost calculation method, inaccuracy of construction cost ratio method, and inactivation of cost plus fixed fee method were analyzed. Therefore, it is difficult to calculate the fair value reflecting the characteristics of the project when calculating the construction design price. Therefore, the price criterion should be improved so that the fair value of the design can be determined according to the contents of the project, By analyzing the correlation and multiple regression analysis of the projects and price information of the completed road construction design, the factors influencing the design price and the level of influence were analyzed.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.