• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.482-482
• /
• 2017

기후변화로 인하여 가뭄 또는 홍수 등의 유역 수자원 피해가 빈번하게 발생하고 있기 때문에 이에 대응하기 위한 예측 및 적응방안 마련이 시급하다. 따라서 본 연구에서는 유역의 물이용 취약성을 평가하고자 하였으며, 평가 지표는 취약성 정의에 따라 노출, 민감도, 적응능력으로 구성하였다. 일반적으로 미래 시나리오 적용 시 기후변화 요소는 고려하고 있으나 사회경제적 요소는 거의 반영되지 않고 있다. 이에 본 연구에서는 강수 패턴의 변화를 반영한 기후변화 시나리오와 인구, 경제, 토지이용변화에 대한 사회경제 시나리오의 적용가능성을 고려하여 지표를 선정하였다. 이후 물이용 취약성의 정량적 평가를 위하여 다기준 의사결정기법(Multi-Criteria Decision Making)인 TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) 기법을 활용하여 취약성을 지수화하였다. 자료는 국가 통계 및 관측 자료와 각 시나리오를 통해 수집하였고, 유출량 등의 모의 자료는 SWAT(Soil and Water Assessment Tool) 모형의 결과를 활용하였다. 타 유역에 비하여 기후변화 및 사회경제적 요소에 대한 영향이 큰 한강유역에 대하여 중권역별 물이용 취약성 순위를 도출하였다. 이를 통하여 기후변화 및 사회경제 시나리오를 적용한 물이용 취약성을 평가하고, 각 시나리오의 상대적 중요성을 분석하였다.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Korea Water Resources Association
• /
• v.48 no.8
• /
• pp.647-657
• /
• 2015

This study assessed the water use vulnerability for 12 basins of South Korea. The annual runoff of 12 basins are derived using a Soil and Water Assessment Tool (SWAT) and the calculated runoff per unit area and population are compared with each basin. The 18 indicators are selected in order to assess the vulnerability. Those are classified by aspects of demand, loss and supply of water use. Their weighting values used Entropy method to determine objective weights. To quantitatively assess the water use vulnerability, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) based on multi-criteria decision making are applied. The results show that the water availability vulnerability of Hyeongsan River has the highest value followed by Sapgyo River; Dongjin River; Seomjin River; Anseong River; Mangyung River; Nakdong River; Tamjin River; Youngsan River, Geum River; Taehwa River; and Han River. The result of this study has a capability to provide references for the index deveopment of climate change vulnerability assessment.

• Journal of Korea Water Resources Association
• /
• v.39 no.11 s.172
• /
• pp.947-960
• /
• 2006

This study shows the application of sustainable water resource planning procedure developed in the previous paper. Its goal is to prevent the streamflow depletion in upstream watershed of the Anyangcheon which is a typical urban stream. The pressure-state-response model which is the framework to reflect the sustainability was applied. The composite programming which is the multilevel multicriteria decision making technique is also used in the calculation of state and evaluation index. The feasible alternatives were proposed and hydrologically analyzed by SWAT(Soil and Water Assessment Tool) and the priority ranking of alternatives were proposed based on the results of SWAT.

• Proceedings of the KAIS Fall Conference
• /
• 2009.05a
• /
• pp.817-820
• /
• 2009

신종 및 재출현 전염병이 지속적으로 유행하고 해외 전염병의 국내유입가능성이 증대됨에 따라 국립검역소의 검역관리 사업의 효율성 평가는 매우 중요하다. 연구는 평가 구성요소 사이의 상대적 중요도, 즉 가중치(weight) 부여에 있어서 과학적 타당성을 인정받고 있는 계층분석절차(Analytical Hierarchy Process; AHP) 기법에 의한 이원비교방법을 사용하여 설정하였다. AHP기법은 복잡한 다기준 의사결정문제(multi-criteria decision making problem)를 계층화하여 단순화 체계화시킴으로써 그 영향도를 계량화하는데 탁월한 기법이라는 평가를 받고 있다. 실제 측정에 있어서는 본 모형을 이용하여 얻어졌다. 대영역(기관평가영역, 서비스 및 프로그램평가 영역), 중영역(투입, 과정, 결과, 검역업무, 검사업무, 위생관리업무, 병원체조사감시업무, 전염병예방홍보 교육업무)으로 구분하여 최종적으로 평가지표로 선정된 지표는 실제 국립검역소 사업에 적용하였으며, 이에 대한 최소한의 평가지표를 최종 선정하여 향후 국립검역소사업 평가체계를 보다 체계화 하였다.

• The Journal of Bigdata
• /
• v.8 no.1
• /
• pp.111-129
• /
• 2023

With the diffusion of digital innovation, the adoption of innovative medical technologies based on artificial intelligence is increasing in the medical field. This is driving the launch and adoption of AI-based SaMD(Software as a Medical Device), but there is a lack of research on the factors that influence the adoption of SaMD by medical institutions. The purpose of this study is to identify key factors that influence medical institutions' decisions to adopt AI-based SaMDs, and to analyze the weights and priorities of these factors. For this purpose, we conducted Delphi surveys based on the results of literature studies on technology acceptance models in healthcare industry, medical AI and SaMD, and developed a research model by combining HOTE(Human, Organization, Technology and Environment) framework and HABIO(Holistic Approach {Business, Information, Organizational}) framework. Based on the research model with 5 main criteria and 22 sub-criteria, we conducted an AHP(Analytical Hierarchy Process) analysis among the experts from domestic medical institutions and SaMD providers to empirically analyze SaMD adoption factors. The results of this study showed that the priority of the main criteria for determining the adoption of AI-based SaMD was in the order of technical factors, economic factors, human factors, organizational factors, and environmental factors. The priority of sub-criteria was in the order of reliability, cost reduction, medical staff's acceptance, safety, top management's support, security, and licensing & regulatory levels. Specifically, technical factors such as reliability, safety, and security were found to be the most important factors for SaMD adoption. In addition, the comparisons and analyses of the weights and priorities of each group showed that the weights and priorities of SaMD adoption factors varied by type of institution, type of medical institution, and type of job in the medical institution.

• Spatial Information Research
• /
• v.20 no.6
• /
• pp.33-43
• /
• 2012

As part of recent sustainable transport, bike has come into the spotlight as a green transport at close range to link between walking and public transit and also alterative to solve problems of existing vehicle travel. Some arguments on promotion of using bicycles have already been made in Europe, the U.S and other developed countries. To be sure, much has been written extensively in description of utilization of bike oriented by supplier, for examples, Level of Service with bike path, infrastructure such as bicycle racks and lounge etc. Therefore, our study has been differentiated in development of new evaluation model focused on level of bike user's satisfaction, comprehensively considering suitability for bikeway installation, connectivity of the public transportation system and stability in Incheon City. ANP(Analytic Network Process) analysis which is able to allow consideration of the interdependence of criteria has been hired due to multi-collinearity instead of AHP used in multi-criteria decision analysis. Last but not least, we drew bike route on a case-by-case for maintenance and improvement of its facility in Namdong-gu and Bupyeong-gu. To conclude, suggested finding has dem onstrated the validity of evaluation scheme for bikeways which is appropriate for type and purpose and ultimately this can be used to establish policy decision making for improvement of bikeway.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.3
• /
• pp.249-273
• /
• 2004

Finding an optimal solution in MADN[(Multi-Attribute Decision-Making) problems is difficult, when the number of alternatives, or that of attributes is relatively large Most of the existing mathematical approaches arrive at a final solution on the basis of many unrealistic assumptions, without reflecting the decision-maker's preference structure exactly. In this paper we suggest a model that helps us find a group consensus without assessing these parameters in specific cardinal values. Therefore, This research provides a comprehensive Decision Making of the theory and methods applicable to the analysis of decisions that involve risk and multiple criteria attributes. after, The emphasis of the procedure will be on developments from the fields of decisions analysis and utility theory of Taguchi Method. This theoretical development will be illustrated through the discussion of several real-world application and a case study. When the multiple number of decision makers are involved in the decision making procedure, the problem of uncertainties invariably occurs, because of the different views between them. In this paper, New decision making model using Taguchi Method is applied to effectively model the multi-attribute-decision making(MADM) procedure in the uncertainties dominated two area(quantitative and qualitative factors), Quantitative factors evaluation is used Loss Function of Taguchi, qualitative factors evaluation is used 50 ratio by each specialist. thus it can be used for aiding of preferable alternative. as a result, We will be proved efficiency about New decision making model of applied Taguchi Method with Analytical presentation of all the expecting outcomes when a specific strategy or an alternative plan is selected under expecting future environment.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.306-306
• /
• 2019

전지구적 기온상승으로 인해 미래기후의 관한 연구가 중요시 되고 있다. 위와 같은 현상으로 인하여 다양한 기후변화 연구가 진행되고 있다. 미래기후 연구에는 GCM (General Circulation Model) 모의 결과가 이용된다. 격자 자료로 구성된 GCM은 연구 지점으로 지역적 상세화와 연구지역의 관측자료 사이의 편이 보정(bias correction)이 필수적이다. 위와 같은 근거로 편이 보정 방법의 선택은 매우 중요하며 편의 보정의 방법에 따라서 결과가 다르게 도출될 수 있다. 또한 국내외 연구에서는 다양한 상세화 기법과 편이 보정 기법을 분석 및 평가하는 연구가 진행되고 있으며, 편의 기법 중 대표적인 기법인 Quantile mapping과 Random Forest 기법이 있다. Quantile mapping 기법은 GCM의 과거 모의 데이터와의 편이 보정에 있어서 우수하게 나타났으나, GCM 데이터의 미래 예측 기간(2010년~2018년)까지의 데이터에서는 극한 강수를 정량적으로 분석 가능한 Random Forest 기법이 편이 보정 과정에서 성능이 우수할 것으로 판단된다. 본 연구에서는 우리나라 21개 관측소를 기준으로 총 4개의 GCM(GISS, CSIRO, CCSM4,MIROC5)의 과거 기간 자료(1970년~2005년)를 실제 관측소에서 관측된 강수량을 편의 보정하는 방법에 있어서 편의 보정 기법의 성능을 비교한 결과와 GCM 미래 예측 기간 자료(2010년~2018년)에서의 편의 보정 기법의 성능 결과를 비교하였다. 이를 토대로 편이 보정 기법의 결과를 6개의 평가지수를 이용하여 정량적으로 분석하였으며, 다기준의사결정기법인 TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution)를 이용하여 편이 보정기법들의 성능에 있어서 우선순위를 선정하였다. 본 연구에서 편이 보정 방법으로 Quantile mapping 방법을 사용했으며, Quantile mapping의 기법으로는 비모수 변환법(non-parametric transformation)과 분포기반 변환법(distribution derived transformation)이 사용되었다. 또한 머신러닝 방법 중 하나인 Random Forest 방법을 동시에 사용하여 결과를 비교하였다. 또한 GCM 자료가 격자식으로 제공하고 있기 때문에 관측소 강수량도 공간적으로 환산하여야 하는데, 본 연구에서는 역거리 가중치법(inverse distance weighting, IDW) 방법을 이용하였다.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.22 no.1
• /
• pp.107-120
• /
• 2020

In a performance-based evaluation of structures in use, the current performance is assessed by summing up the weighting of the evaluation indices for each performance. In this study, to suggest a performance-based evaluation technique for NATM tunnels in use, the performance evaluation indices were derived by examining the characteristics and similarities of each index developed from previous study. The weighting of the evaluation indices was derived by calculating the relative importance of each evaluation indices from the AHP analysis. In order to develop a quantitative evaluation model, grading criteria for each performance index was derived through literature review, and performance evaluation tables for road and railway tunnels were presented. In order to verify the significance of the proposed performance evaluation model, the correlation analysis was performed between each evaluation index and the final evaluation result. In the correlation analysis, the survey data measured through precision safety diagnosis in the tunnel in use was applied. It may be said that the proposed evaluation indices, weighting, criteria and evaluation models for tunnels in use can be applied to the performance-based maintenance system of tunnels.