• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.657-660
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• 2004

규칙기반의 상품추천시스템은 많은 인터넷 쇼핑몰에서 활용되고 있지만 규칙을 추출할 수 있는 마케팅 전문가 확보와 방대한 양의 고객 데이터 처리의 어려움으로 유용한 규칙을 찾는 것이 매우 어렵다. 본 연구에서는 이러한 규칙기반 상품추천시스템의 단점을 보완할 수 있는 방법으로 전역 최적화 기법의 하나인 유전자 알고리즘을 활용하여 고객정보를 토대로 추천 규칙을 도출할 수 있는 방안을 제시한다. 또한 본 연구에서 제안한 유전자 알고리즘에 기반한 추천 규칙들이 장착된 웹 기반의 개인화된 상품추천시스템의 프로토타입을 개발하고 이에 대한 실제 사용자들의 이용 만족도를 확인함으로써 본 연구에서 제안한 방법론의 유용성을 확인하고자 한다.

• Journal of Cadastre & Land InformatiX
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• v.51 no.2
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• pp.83-106
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• 2021

Interests in clean fuels have been soaring because of environmental problems such as air pollution and global warming. Unlike fossil fuels, hydrogen obtains public attention as a eco-friendly energy source because it releases only water when burned. Various policy efforts have been made to establish a hydrogen based transportation network. The station that supplies hydrogen to hydrogen-powered trucks is essential for building the hydrogen based logistics system. Thus, determining the optimal location of refueling stations is an important topic in the network. Although previous studies have mostly applied optimization based methodologies, this paper adopts machine learning to review spatial attributes of candidate locations in selecting the optimal position of the refueling stations. Machine learning shows outstanding performance in various fields. However, it has not yet applied to an optimal location selection problem of hydrogen refueling stations. Therefore, several machine learning models are applied and compared in performance by setting variables relevant to the location of highway rest areas and random points on a highway. The results show that Random Forest model is superior in terms of F1-score. We believe that this work can be a starting point to utilize machine learning based methods as the preliminary review for the optimal sites of the stations before the optimization applies.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.7
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• pp.18-27
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• 2006

The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods, therefore it is hard to apply directly to large-scaled problems such as an aerodynamic shape design optimization. In this study, to overcome this computational limitation the efficient RBDO procedure with the two-point approximation(TPA) and adjoint sensitivity analysis is proposed, that the computational requirement is nearly the same as DO and the reliability accuracy is good compared with that of RBDO. Using this, the 3-D aerodynamic shape design optimization is performed very efficiently.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.1017-1021
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• 2009

일반적인 설계 홍수량 산정 절차는 분석하고자 하는 대상유역의 수문자료 중 홍수량 자료가 존재하지 않을 경우 강우빈도해석을 실시하고, 만약 홍수량 자료가 존재한다면 유출을 통계분석하여 홍수빈도 해석을 실시하여야 한다. 본 연구에서는 1999$^{\sim}$2008년까지 수위-유량 관측을 실시하여 유출자료를 비교적 충분히 보유하고 있는 서울시 관내 지방하천인 우이천 유역을 대상으로 수위-유량관계곡선을 작성하여 과거 호우사상을 토대로 강우-유출모형의 매개변수를 최적화하였으며, 최적화된 모형을 이용하여 기상청관할 서울지점 시간강우관측 자료를 입력 자료로 유출모의를 실시하였다. 모의된 홍수량계열과 관측유량계열을 사용하여 연최대홍수계열을 구축한 후 홍수빈도해석을 실시하였다. 분석결과 기존의 '확률강우량-단위도' 방법에 비하여 불확실성이 제거된 확률홍수량 추정치의 결과를 얻을 수 있었다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.6
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• pp.539-544
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• 2013

This study provides a solution method for the inverse heat conduction problem based on a combination of a public domain CAE (computer aided engineering) software and a commercial CAO (computer aided optimization) software. The solver system has been implemented without any in-house coding. The proposed method is simple to implement. Moreover, it can be easily reproduced.

• Applied Chemistry for Engineering
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• v.28 no.1
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• pp.17-22
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• 2017

This review deals with scale-up strategies for optimized chemical processes particularly for micron and submicron products. The method of finding scale-up factors was also introduced for two systems, a system with chemical reaction and a system without chemical reaction. This review is expected to serve as an initial guideline for process engineers who are to scale up their current chemical processes for small products of micron or submicron size.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.644-645
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• 2021

In this paper, we propose a hardware structure of a watermarking processor based on deep learning technology to protect the intellectual property rights of ultra-high resolution digital images and videos. We propose an optimization methodology to implement a deep learning-based watermarking algorithm in hardware.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.311-311
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• 2020

가뭄·홍수 등 수재해 대응대책 수립 측면에서 유역의 자연유출량 산정은 가장 핵심적인 사항이라 할 수 있다. 우리나라는 전국적으로 수위-유량관측소를 설치하여 실시간 유출량 모니터링을 통해 수문정보를 수집하며, 주요지점을 제외한 유역에서는 주기적으로 강우-유출모형의 매개변수 최적화를 통해 산정된 장기유출량 결과를 자연유출으로 가정하여 수자원 계획 수립시 활용하고 있다. 그러나 강우-유출모형의 최적 매개변수 추정을 위해 활용되는 관측 수문자료는 상대적으로 자료의 연한이 짧고, 계절·공간적인 특성으로 인해 매우 제한적이며, 유역의 특성을 충분히 고려하지 못해 미계측유역의 매개변수 추정시 모형의 자료에서 기인한 불확실성이 크게 발생한다는 단점이 있다. 이에 본 연구에서는 관측자료에 대한 신뢰성이 유의하며, 공간적으로 고르게 분포된 12개 댐 유역을 대상으로 매개변수 지역화 연구를 수행하였다. SCEM-UA기법을 통해 GR4J 강우-유출모형의 매개변수를 최적화 하였으며, 매개변수와의 상관관계 및 선형회귀분석을 통해 유역특성인자를 선별하여 Copula 함수를 통해 지역화된 매개변수를 추정하였다. 최종적으로 본 연구에서 제시된 방법론에 대한 적합성을 평가하기 위하여 매개변수 최적화가 수행된 유역을 미계측 유역으로 가정하여 교차검증 관점에서 적합성을 검토하였으며, 통계적으로 유의한 결과가 도출되는 것을 확인하였다.

• Information Systems Review
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• v.8 no.2
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• pp.103-117
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• 2006

As the interest in the combinatorial auction has increased, diverse combinatorial auction market types have been proposed. Although there have been several studies on the combinatorial auction design, the studies covered some factors or partial dimensions of combinatorial auction design. Given the potential practical value of combinatorial auctions, it is necessary to approach it with an integrated and systematic design methodology for supporting a comprehensive range of combinatorial auction models. Thus, we present a systematic framework for combinatorial auction design methodology. In particular, we classified the combinatorial auction architecture types, process types, and mechanism types. This framework characterizes the different combinatorial auction models, and lead to a useful taxonomy of the combinatorial auction design factors and taxonomy of the market types by coordination among the design factors. In addition, we illustrate an n-bilateral combinatorial auction market, derived from our design methodology, to show the viability of our study.