• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.407-410
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• 2006

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine teaming, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for four data sets with good performance results

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.219-219
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• 2017

This study aims at examining each firm's decision-makings of complex product and system (hereafter CoPS) innovation strategy, so that it tries to reveal the nature and role of CoPS innovations strategy. And it designed a comparative case study along with qualitative methods, by having two mobile operators' digital rights management (hereafter DRM) innovation in South Korea's digital music service industry. Through literature review, this study formulated three research propositions: (i) Each firm's decision-makings of CoPS innovations strategy are analytical negotiation process among economic actors in an industry; (ii) Each firm's market power originated from its market share from the installed base through network effect and switching cost influence decision-makings of CoPS innovation strategies; (iii) Each firm's decision-makings of different CoPS innovation strategies are related to their intension of achieving better market power, consequently dominant design. Through empirical examination of two mobile operators' decision-makings of DRM innovation strategy, this study empirically verified three research propositions.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.54-59
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• 2006

Decision tree is one of the most effective and widely used methods for building classification model. Researchers from various disciplines such as statistics, machine learning, pattern recognition, and data mining have considered the decision tree method as an effective solution to their field problems. In this paper, an application of decision tree method to classify the faults of induction motors is proposed. The original data from experiment is dealt with feature calculation to get the useful information as attributes. These data are then assigned the classes which are based on our experience before becoming data inputs for decision tree. The total 9 classes are defined. An implementation of decision tree written in Matlab is used for these data.

• Journal of Ship and Ocean Technology
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• v.5 no.1
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• pp.30-37
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• 2001

Ship optimal design is a multi-objective decision-making process and its optimal solution does not exit in general. It is a problem in which the decision-maker is very interested that an effective solution is how to be found which has good characteristic and is substituted for optimal solution in a sense. In the previous methods of multi-objective decision-making, the weighting coefficients are decided from the point of view of individuals which have a bit sub-jective an unilateral behavior. in order to fairly and objectively decide the weighting coeffi-cients, which are considered to be optimal in all system of multi-objective decision-making and satisfactory solution to the decision-maker, the pater presents a method of applying the Technology of the Biggest Entropy. It is proved that the method described in the paper is very feasible and effective be means of a practical example of ship optimal design.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2007.04a
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• pp.101-104
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• 2007

As the proportion of underground construction increases, the impact of inappropriate selection of a underground construction method for a construction size increases. The purpose of this study is to develop an objective way of selecting an excavation method. There have been several attempts to achieve the same goal using various data mining methods such as the artificial neural network, the support vector machine, and the case-based reasoning. However, they focused only on the selection of a retaining wall construction method out of six types of retaining walls. When we categorized an underground construction work into four groups and added more number of independent variables (i.e., more number of construction methods), the predictability decreased. As an alternative, we developed a decision tree by analyzing 25 earthwork cases with detailed information. We implemented the developed decision tree as a computer-supported program called Dr. underground and are still in the process of validating and revising the decision tree. This study is still in a preliminary stage and will be improved by collecting and analyzing more cases.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.2
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• pp.144-149
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• 2008

Purpose: The aim of this study was to testify correlations between critical thinking disposition and decision making styles. Methods: The subjects of this study were 193 freshman nursing students in the 1 nursing school located in Incheon area. The data were collected by self-reporting questionnaires. The data were analyzed using descriptive statistics and Pearson correlation coefficient analysis. Results: The score of critical thinking disposition was revealed 3.96 points. The highest was inquisitiveness, the lowest was systematicity. The most frequent decision making style was revealed a rational decision making. The next was dependant decision making, intuitional decision making as follows. The critical thinking disposition and rational decision making had a statistically significant positive correlation. However the critical thinking disposition and dependant decision making had a statistically significant negative correlation. Conclusion: With these findings, we are found that the more increasing critical thinking disposition, the more developing rational decision making. It will suggested that the program for increasing nursing student's critical thinking disposition focused on systematicity, analyticity and truth seeking in critical thinking sub categories.

• Physical Therapy Rehabilitation Science
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• v.12 no.2
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• pp.80-91
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• 2023

Objective: The purpose of this study is to identify factors that affect the incidence of hypertension using logistic regression and decision tree analysis, and to build and compare predictive models. Design: Secondary data analysis study Methods: We analyzed 9,859 subjects from the Korean health panel annual 2019 data provided by the Korea Institute for Health and Social Affairs and National Health Insurance Service. Frequency analysis, chi-square test, binary logistic regression, and decision tree analysis were performed on the data. Results: In logistic regression analysis, those who were 60 years of age or older (Odds ratio, OR=68.801, p<0.001), those who were divorced/widowhood/separated (OR=1.377, p<0.001), those who graduated from middle school or younger (OR=1, reference), those who did not walk at all (OR=1, reference), those who were obese (OR=5.109, p<0.001), and those who had poor subjective health status (OR=2.163, p<0.001) were more likely to develop hypertension. In the decision tree, those over 60 years of age, overweight or obese, and those who graduated from middle school or younger had the highest probability of developing hypertension at 83.3%. Logistic regression analysis showed a specificity of 85.3% and sensitivity of 47.9%; while decision tree analysis showed a specificity of 81.9% and sensitivity of 52.9%. In classification accuracy, logistic regression and decision tree analysis showed 73.6% and 72.6% prediction, respectively. Conclusions: Both logistic regression and decision tree analysis were adequate to explain the predictive model. It is thought that both analysis methods can be used as useful data for constructing a predictive model for hypertension.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.57-62
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• 2010

Recently, decision tree techniques have been studied in terms of quick searching and extracting of massive data in medical fields. Although many different techniques have been developed such as CART, C4.5 and CHAID which are belong to a pie in Clermont decision tree classification algorithm, those methods can jeopardize remained data by the binary method during procedures. In brief, C4.5 method composes a decision tree by entropy levels. In contrast, CART method does by entropy matrix in categorical or continuous data. Therefore, we compared C4.5 and CART methods which were belong to a same pie using breast cancer data to evaluate their performance respectively. To convince data accuracy, we performed cross-validation of results in this paper.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.85-105
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• 2017

Monitoring is the most important part of the construction and operation of the embankment dams. Applied instruments in these dams should be determined based on dam requirements and specifications. Instruments selection considered as one of the most important steps of monitoring plan. Competent instruments selection for dams is very important, as inappropriate selection causes irreparable loss in critical condition. Lack of a systematic method for determining instruments has been considered as a problem for creating an efficient selection. Nowadays, decision making methods have been used widely in different sciences for optimal determination and selection. In this study, the Multi-Attribute Decision Making is applied by considering 9 criteria and categorisation of 8 groups of geotechnical instruments. Therefore, the Analytic Hierarchy Process and Multi-Criteria Optimisation and Compromise Solution methods are employed in order to determine the attributes' importance weights and to prioritise of instruments for embankment dams, respectively. This framework was applied for a rock fill with clay core dam. The results indicated that group decision making optimizes the selection and prioritisation of monitoring instruments for embankment dams, and selected instruments are reliable based on the dam specifications.

• Journal of Distribution Science
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• v.17 no.4
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• pp.27-32
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• 2019

Purpose - The business model is a method of creating corporate value, in existing "classification of business model", limitations and redundancy phenomena are applied when a new type flows in, and as consumer's purchasing decision of consumer behavior 5 steps. The classification schemes can be used for more accurate data analysis by proposing a new mapping technique in the fourth industry. Research design, data, and methodology - It was far more classified on the business model (BMS by BDS), and so on. Designing the new horizons of logistics, marketing, methodology by reclassifying these existing data to new useful data with the old methods, in order to analyze the areas where the problem has been raised for the point that the existing methods are not suitable configured. This will be applicable to the system of quaternary industry from the perspective of the buyer. Results - The mapping results of the consumer purchase decision were as follows,the 1^st stage (interest) was 23.73%, 2^nd stages (publicity) 33.90%, 3^rd stages (sales) 13.56%, 4^th stages (decision) 11.86%, 5^th stages (repurchaser) 16.95%. This verified that "the business model can be classified through "BMS by BDS". Conclusions - This structural classification is the basis of logistics marketing in the 4th industry, and proposes a innovative and effective model of constructing theory.