• Water for future
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• v.25 no.1
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• pp.83-92
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• 1992

Selection of the best operation rule among a set of alternatives for a multipurpose reservoir system operation requires to evaluate many minor criteria I n addition to the major objectives assessed to the system, These problems are sufficiently complex and difficult that they are beyond heuristic decision rules and experiences in case several noncommensurable multiple criteria are included in the evaluation. With the assistance of multicriterion decision analysis techniques, it is possible to select the best one among various alternatives by systematically comparing and ranking the alternatives with respect to the criteria of choice. Evaluation criteria for multipurpose reservoir system operating rules were identified and defined, and the multicriterion decision analysis techniques were applied to evaluate the fore developed operating rules of the existing Chungju multipurpose project according to the identified nine multiple criteria. The application result shows that the methodology is very efficient to select the best operation alternative among a finite number of operating rules with many evaluation criteria for a large scale reservoir system operation.

• Korean Journal of Construction Engineering and Management
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• v.12 no.5
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• pp.127-136
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• 2011

The purpose of this study is analyzed the importance ratio factors of sales price for apartment building construction projects. For this Study, Nine apartment buildings that sold in Seoul, Gyenggi, Chuncheong is selected. The study suggested eight influence factors through interview with experts, research related references, and analysis of cases. Based on those factors, Importance analysis is performed by using AHP method. The result of this study are as follows: 1) Influence factors of sales price are drawn as cost, site, housing, transportation, region, ground, policy, investment factor. 2) In the case of Seoul, The priority order of price influence factors consist of investment factor(16.0%), policy factor(14.6%), and cost factor(13.9%). In the case of Gyenggi, The priority order of sales price influence factors consist of region factor(15.9%), transportation factor(13.8%), and investment factor(13.4%). In the case of Chungcheong, The priority order of sales price influence factors consist of region factor(17.1%), transportation factor(16.4%), and housing factor(14.9%).

• Journal of Korean Tunnelling and Underground Space Association
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• v.7 no.1
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• pp.89-96
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• 2005

Due to fast development of digital equipments, various information techniques have been applied to the tunneling and a decision aid system based on IT has also been used during excavation stage. A PDA based informative tunneling method is, therefore, studied in this paper and the decision aids for tunneling using digital face mapping data as well as geologic information in terms of digital data is developed. For this, wireless network, mobile computer, CDMA and digital camera have been combined to generate the digital map of the tunnel face and reinforcement or excavation pattern can be estimated based on digitalized geologic conditions. Future studies will be concentrated on the enhancement of the PDA S/W so that reinforcement method as well as the amount of reinforcements can also be stored in the same DB. Furthermore, field application of the S/W will be undertaken and a virtual reality technique will also be introduced to visualize all the tunneling work on the computer monitor.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.81-88
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• 2021

Convertible bonds are financial products that contain the nature of both bonds and shares, which are generally issued by companies with lower credit ratings to increase liquidity. Conversion bonds rely on qualitative judgment in the past, although decision-making on whether and when to exercise the right to convert is the most important issue. Therefore, this paper proposes to apply artificial neural network techniques to scientifically determine the exercise of conversion rights. We distinguish between a total of 1,800 learning data published in the past and 200 predictive experimental data and build an artificial neural network learning model. As a result, the parity performance in most groups was excellent, achieving an average excess of about 10% or more. In particular, groups 3-6 recorded an average excess of about 20% and group 6 recorded an average excess of about 37%. This paper is meaningful in that it focused on solving decision problems by converging and applying machine learning techniques, a representative technology of the fourth industry, to the financial sector.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.388-398
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• 2012

In this study, Entropy method and PROMETHEE(Preference Ranking organization METHod for Enrichment Evaluations) which is one of the multi criteria decision making methods are applied to estimate the relative inundation risk ranking of the urban sewer systems. Then, the evaluation factors were selected considering two main items to estimate the inundation risk using Entropy and PROMETHEE. In the first item considering topographical and environmental factor, average elevation, average slope, width of area, population, density of conduit were selected as the detailed factors of first item which have influence of the overflow occurrence and damage scale in urban sewer system. And, the relative reliability of sewer network was considered as the second item which can quantify the inundation appearance. Then, the reliability is estimated considering the number of overflow nodes and overflow volume simultaneously. Therefore, the suggested inundation risk evaluation method can be used as the evaluation index for sewer networks and contribute to decision making for the sewer rehabilitation policy.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1341-1348
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• 2013

To solve the classification problems, various data mining techniques have been applied to database marketing, credit scoring and market forecasting. In this paper, we compare various techniques such as bagging, boosting, LASSO, random forest and support vector machine with the daily lens transaction data. The classical techniques-decision tree, logistic regression-are used too. The experiment shows that the random forest has a little smaller misclassification rate and standard error than those of other methods. The performance of the SVM is good in the sense of misclassfication rate and bad in the sense of standard error. Taking the model interpretation and computing time into consideration, we conclude that the LASSO gives the best result.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.411-425
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• 2013

The importance and necessity of the credit loan are increasing over time. Also, it is a natural consequence that the increase of the risk for borrower increases the risk of non-performing loan. Thus, we need to predict accurately in order to prevent the loss of a credit loan company. Our final goal is to build reliable and accurate prediction model, so we proceed the following steps: At first, we can get an appropriate sample by using several resampling methods. Second, we can consider variety models and tools to fit our resampling data. Finally, in order to find the best model for our real data, various models were compared and assessed.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.287-295
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• 2012

This study aims to develop the methods for effective patient flow in the medical center through simulation modeling. To achieve this, we developed three simulation scenarios based on max/min processing time and addition of X-ray by 15 patient tracks from real hospital data. The simulation software used in this study is Flexsim HC 2.7. According to the scenario 1 on 15 patient tracks' LOS by max processing time, there is a great difference between average length of stay(LOS) and max LOS. And average LOS increases greatly depending on the number of patients by the hours. There is no need to add extra X-ray because the addition of X-ray has not much influence in average LOS. It is possible to make good decisions on patient flow management and medical equipment purchasing through simulation modeling. The concrete simulation scenario as a tool for decision support will contribute to efficiency in hospital management.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.21-32
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• 2003

This paper discusses the design of location optimization visualization and feasibility of 3 dimensional visualization techniques. In generic GIS visualization of location analysis, 2 dimensional visualization techniques have been used to map location elements and model solution, such as displaying demand and supply points, drawing connecting lines(e. g. spider line) of optimal locations to their demands, and representing density of location variations. Nevertheless, current GIS and location analysis literatures have little attentions in 3D visualization applications for location optimization problems. Previous research has been neglected 3D visualization of solution performances and its evaluation of solution quality. Consequently, this paper demonstrates potential benefits of 3D visualization techniques and its appropriate GIS applications for location optimization analysis. The visualization effectiveness of 3D approaches is examined in terms of spatial accessibility, and solution performance of optimal location models is evaluated. Finally, this paper proposes extensive 3D visualization perspectives for location analysis and GIS research as a further research agenda.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.322-322
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• 2016

국내 1, 2종 댐 시설물은 "시설물의 안전관리에 관한 특별법(이하 시특법)" 제7조에 의해 주기적으로 정밀안전진단을 실시하여 상태평가 및 안전성평가에 의한 종합평가 등급을 부여하고 있다. 정밀안전진단 중 안전성 평가의 수문학적 안전성 평가는 댐의 구조형식과 현장진단 결과에 의한 댐의 상태평가에 따라 1차적으로 수행된다. 여유고 부족 또는 월류 발생 등의 1차적인 조건을 만족시키지 못할 경우 그에 따른 댐체의 구조적 안전을 검토(콘크리트댐)하고, 최종적으로 댐 붕괴 발생 시 하류에 미치는 인적, 경제적 위험요인 등을 기준으로 평가하는 3단계 평가가 수행된다. 본 논문에서는 위 단계적 평가가 수행된 기존댐의 수문학적 안전성 평가 및 상태평가 결과를 사용하여, 1종 기존댐에 대한 수문학적 안전성 취약 순위를 선정하고자 한다. 취약 순위를 선정하기 위하여 다기준의사결정기법(Multi-Criteria Decision Making: 이하 MCDM)을 적용하였고, MC DM의 Payoff Matrix 설정을 위하여 수문학적 안전성 평가 지표를 기준으로 설정하였으며, 이 외의 기준으로는 대상 댐의 연최대 강수량 값을 사용하였다. 연최대강수량값을 산정하기 위하여 기상관측소별 연최대 강수량 30년치의 평균값을 kriging 기법에 적용하여 대상댐에 대한 연최대강수량 값을 도출하여 수문학적 안전성 평가 지표 및 기존댐의 기상 관측값에 따른 댐별 수문학적 안전성 취약 순위 선정에 관한 연구를 수행하였다. 위 결과를 활용하여 수문학적 안전성 평가등급에 대한 검토 및 기후변화 적응 댐 수문학적 안전성 평가 프레임워크 개발을 위한 기초 자료로 활용될 것으로 기대된다.