• Journal of the Economic Geographical Society of Korea
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• v.21 no.2
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• pp.90-106
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• 2018

This study suggests a gateway strategy for transporting agri-food exports to expand exports after examining the patterns of Korean agri-food exports by commodities and the role of export gateways. Korean agri-food exports have increased, but processed food exports have increased significantly compared to fresh agricultural products during the last 17 years. More importantly, Busan port is the main agri-food export hub in Korea. Under these circumstances, this paper examines the determinants of processed cereal-based food (HS 19) exports through Busan port using classification and regression tree (CART) analysis. As a result, the main factors that help to predict the real value of Korean exports are the GDP of the export destination countries, their distances from Korea and their GNI per capita. The destinations of Korean agri-food exports are finally classified into eight groups, which reveals the characteristics of clusters and provides useful insights for the strategies to expand agri-food exports.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.55-69
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• 2013

Managers are required to adopt and implement the human resource management practice that fit firm's strategy the most, so that optimize overall performance. However, the time and relative resources that any firm has are limited, which demands managers to understand the relative importance of all sorts of HR practice and promote them in an order of their relative importance. This study follows the universal perspective and contingency perspective(according to firm size and strategy type), try to identify the most effective HR practice on performance as well as their relative importance by "CART Ensemble" analysis. The results are as follows. From universal perspective, firms always need to high level of integration between strategy and HR department, decision making participation, autonomy of speed of working, and autonomy of way of working. Contingency perspective also suggested the importance of integration between HRM and strategy. But others are different case by case. This study suggests useful implications for managers.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.291-300
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• 1999

본 논문은 인공신경망과 귀납적 학습방법 등의 인공지능 방법과 선물가격결정에 대한 기존 재무이론을 사용하여 일상어휘로 표현되는 파생상품 가격예측 모형을 개발하는데 있다. 모형의 개발은 1단계로 인공신경망이나 기존의 선물가격결정이론(평균보유비용모형이나 일반균형모형)을 이용하여 선물 가격을 예측한 후, 서로 비교분석하여 인공신경망 모형의 우수성을 확인하였다. 귀납적 학습방법중 CART 알고리듬을 사용하여 If-Then 규칙을 생성하였다. 특히 실용적 측면에서 선물가격의 일상어휘화를 통한 모형개발을 여러 가지 방법으로 시도하였다. 이러한 선물가격 예측모형의 유용성은 일단 If-Then 규칙으로 표현되어 전문가의 판단에 확실한 이론적인 근거를 제시할 수 있는 장점이 있으며, 특히 의사결정지원시스템으로 활용화 될 경우 매우 유용한 근거자료로 활용될 수 있다. 이러한 선물가격 예측모형은 정확성은 분석표본과 검증표본으로 나누어 검증표본에서 세가지 기본모형(평균보유비용모형, 일반균형모형, 인공신경망 모형)과 각 모형의 귀납적 학습방법 모형의 다른 3가지 어휘표현방법 3가지를 모형별로 비교 분석하였다. 분석결과 인공신경망모형은 상당한 예측력을 갖고 있는 것으로 판명되었으며, 특히 CART를 기반으로 한 일상어휘 기반의 선물가격예측 모형은 예측력이 높은 것으로 나타났다.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.489-496
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• 2011

In designing cultural product, end user experiences, feelings and satisfaction with form are one of the most important factors. However, the design processes of cultural product typically depend on traditional methods or intuitive, designer driven methods for generating and evaluating form concepts. We applied sensibility evaluation, analysis method and contemporary digital vehicle design process to cultural product. This paper describes the implementation process of internet based design support system that helps assess user's sensibilities of forms created in each stages of design process. The form focused sensibility evaluation approach provides designers with fast and various feedbacks about their design in each stage. Practical application for exterior design of tourist cart of slowcity(ciitaslow) Shinan was illustrated.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.9-16
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• 2013

Data analysis is the universal classification techniques, which requires a lot of effort. It can be easily analyzed to understand the results. Decision tree which is developed by Breiman can be the most representative methods. There are two core contents in decision tree. One of the core content is to divide dimensional space of the independent variables repeatedly, Another is pruning using the data for evaluation. In classification problem, the response variables are categorical variables. It should be repeatedly splitting the dimension of the variable space into a multidimensional rectangular non overlapping share. Where the continuous variables, binary, or a scale of sequences, etc. varies. In this paper, we obtain the coefficients of precision, reproducibility and accuracy of the classification tree to classify and evaluate the performance of the new cases, and through experiments to evaluate.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.05a
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• pp.266-273
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• 2005

Data mining techniques enable us to generate useful information for decision support from the data sources which are generated and accumulated in the process of routine organizational management activities. College administration system is a typical example that produces a warehouse of student records as each and every student enters a college and undertakes the curricular and extracurricular activities. So far, these data have been utilized to a very limited student service purposes, such as issuance of transcripts, graduation evaluation, GPA calculation, etc. In this paper, we utilize Holland career search test results, TOEIC score, course work list, and GPA score as the input for data mining and generation the student advisory information. Factor analysis, AHP(Analytic Hierarchy Process), artificial neural net, and CART(Classification And Regression Tree) techniques are deployed in the data mining process. Since these data mining techniques are very powerful in processing and discovering useful knowledge and information from large scale student databases, we can expect a highly sophisticated student advisory knowledge and services which may not be obtained with the human student advice experts.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1775-1776
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• 2006

This paper deals with the problem of friction measurement of an inverted pendulum system using the regression analysis and proposes a solution. The approach taken in this study is getting the friction from a regression relational expression between the motor voltage and the cart velocity of an inverted pendulum system. The result to compensate LQR (linear Quadratic Regulator) controller with the friction which is measured in system, improved the performance of the system. Above all, the study has found that the proposed compensation of the friction reduces the oscillation of the cart position. In conclusion, the proposed method is useful when parameters in the given system model are not known.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.155-156
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• 2019

Traditional machine learning based emotion analysis methods such as Classification and Regression Tree (CART), Support Vector Machine (SVM), and k-nearest neighbor classification (kNN) are less accurate. In this paper, we propose an improved kNN classification method. Improved methods and data normalization achieve the goal of improving accuracy. Then, three classification algorithms and an improved algorithm were compared based on experimental data.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• 한국ITS학회:학술대회논문집
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• 2008.11a
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• pp.1-7
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• 2008