의사결정나무 알고리즘은 데이터마이닝 기법중 하나인데 관심이 되는 데이터들에 대하여 분류 및 예측을 가능하게 해준다. 이 기법은 데이터 형태의 특성을 분석할 수 있고 산업재해 형태의 차이점을 찾아내는데 사용될 수 있다. 본 연구에서는 산업재해 데이터의 특성을 파악하고자 C4.5 알고리즘을 사용하였다. 본 연구에서 분석을 위하여 사용된 데이터는 강원도에서 발생한 2년 동안의 산업재해 관련 데이터로서 연구에 적용된 데이터의 수는 19,909개로 구성되어 있다

The consequences of rapid industrial advancement, diversified types of business and unexpected industrial accidents have caused a lot of damage to many unspecified persons both in a human way and a material way Although various previous studies have been analyzed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. The main objective of this study is to find an optimal algorithm for data analysis of industrial accidents and this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and AnswerTree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work chosen from 19,574 data related to construction industries during three years (2002~2004) in Korea.

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

Due to the convenience of use and rapid access to their information to find, many Internet users utilize the search engines or portal sites to find their information and web sites. However, many researches related with web site evaluation pointed out that many factors have to be considered to increase the usefulness of the site and the degree of user's preference about the site. In this research, based on the previous research, preference factors are derived to evaluate the portal sites. And then, five portal sites are evaluated by the questionnaire. CHAID, a decision tree technique, is used to analyze the results of survey and the relationships of preference factors. This research can be an indicator when we analyze the preference factors of portal site and other kinds of web sites using decision tree.

Classification is an important area in a data mining. There are various ways in classification methodologies : the decision tree and the neural network, etc. Recently, Rough set theory has been presented as a method for classification. Rough set theory is a new approach in decision making in the presence of uncertainty and vagueness. In the process of constructing the tree, appropriate attributes have to be selected as nodes of the tree. In this paper, we present a new approach to selection of attributes for the construction of decision tree using the Rough set theory. The suggested method makes more simple classification rules in the decision tree and reduces the volume of the data to be treated.

Since prolonged exposure to elevated ozone (O3) concentrations is known to be harmful to human health, appropriate control strategies for ozone are needed for the non-attainment area such as Seoul, Korea. The goal of this research is to assess factors linked with the 1-hour ozone exceedance through a decision tree model. Since ozone is a secondary pollutant, lag times between ozone and explanatory variables for ozone formation are taken into account in the model to improve the accuracy of the simulation. Results show that while ozone concentrations of the previous day and NO2 concentrations in the morning are major drivers for ozone exceedances in the early afternoon, meteorology plays more important role for ozone exceedances in the late afternoon. Results also show that a selection of lag times between ozone and explanatory variables affect the accuracy of predicting 1-hour ozone exceedances. The result analyzed in this study can be used for developing control strategies of ozone in Seoul, Korea.

Purpose – This study attempts to examine Islamic banking practices in Iran based on new scientific methods. Design, methodology, and approach – The study used financial ratios demonstrating healthy or non-healthy banks to assess the financial health of banks listed on the Tehran Stock Exchange. The assessment of these ratios with a decision tree as a non-parametric method for modeling is recommended to present this model. Information about the financial health of banks could affect the decisions of different groups of banks’ financial report users including shareholders, auditors, stock exchanges, central banks, and so on. Results – The results of the study show that a decision tree is a strong approach for classifying Islamic banks in Iran. Conclusions – To date, several studies have been conducted in various countries on the topic of this study. Considering the importance of Islamic banking, this is one of the first studies in Iran the outcomes of the study may prove helpful to the Iranian economy.

본 논문에서는 결정트리 학습 알고리즘을 활용한 축구 게임 수비 NPC 제어 방법을 제안한다. 제안하는 방법은 실제 게임 사용자들의 이동 방향 패턴과 행동 패턴을 추출하여 결정트리학습 알고리즘에 적용한다. 그리고 학습된 결정트리를 바탕으로 NPC의 이동방향과 행동을 결정한다. 실험결과 제안하는 방법은 결정트리 학습에 시간이 다소 걸리지만, 학습된 결정트리를 바탕으로 이동방향이나 행동을 결정하는 시간은 약 0.001-0.003 ms(밀리초)가 소요되어 실시간으로 NPC를 제어할 수 있었다. 또한, 제안하는 방법은 현재 상태 정보 뿐만 아니라 이를 분석한 관계정보, 이전 상태 정보도 함께 활용하므로, 기존방법인 (Letia98)에 비해 이동방향 결정시 높은 정확도를 나타냈다.

도로교량의 경우 급속한 도시화로 인해 증가한 교통량을 처리하기 위해 교량확폭과 신설교량의 추가 건설 등의 방법이 사용되고 있다. 하지만 현재 국내에서는 확폭 또는 신설 교량의 추가건설의 타당성을 판단하기 위한 합리적인 절차나 기준이 마련되어 있지 않다. 또한 교량 확폭 공사 시에는 일반적인 교량신설 공사에 비해 불확실성을 내포한 사건들이 추가적으로 존재한다. 이에 본 논문에서는 의사결정수 방법을 이용해 교량확장에 따라 발생 가능한 사건의 기대 위험비용을 체계적으로 고려할 수 있는 개선된 형태의 생애주기비용 분석 모델을 제안하였다.

While increasing demand of the service for the disabled and the elderly people, assistive technologies have been developed rapidly. The natural signal of human such as voice or gesture has been applied to the system for assisting the disabled and the elderly people. As an example of such kind of human robot interface, the Soft Remote Control System has been developed by HWRS-ERC in KAIST[1]. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies of the system is the hand gesture recognition algorithm. The frequently occurred problems which lower the recognition rate of hand gesture are inter-person variation and intra-person variation. Intra-person variation can be handled by inducing fuzzy concept. In this paper, we propose multivariate fuzzy decision tree(MFDT) learning and classification algorithm for hand motion recognition. To recognize hand gesture of a new user, the most proper recognition model among several well trained models is selected using model selection algorithm and incrementally adapted to the user’s hand gesture. For the general performance of MFDT as a classifier, we show classification rate using the benchmark data of the UCI repository. For the performance of hand gesture recognition, we tested using hand gesture data which is collected from 10 people for 15 days. The experimental results show that the classification and user adaptation performance of proposed algorithm is better than general fuzzy decision tree.