• 한국항해학회지
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• 제23권2호
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• pp.11-22
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• 1999

This paper is concerned with the development of a tractable model to assist liner shipping companies in the decision-making of empty container repositioning and leasing. A hybrid methodology is presented which properly accounts for the specific characteristics of empty container management. For this mathematical models are developed based on dynamic network models, covering both land and marine segment. Then a stochastic method is presented to deal with the uncertainty of the future demand and supply. Especially, the concept of opportunity cost has been introduced in order to explain interactions between the variation of the future demand and supply and the stock level at each depot.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.102.1-102
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• 2002

In this paper, we propose Self-organizing neurofuzzy networks(SONFN) and discuss their comprehensive design methodology. The proposed SONFN is generated from the mutually combined structure of both neurofuzzy networks (NFN) and polynomial neural networks(PNN) for model identification of complex and nonlinear systems. NFN contributes to the formation of the premise part of the SONFN. The consequence part of the SONFN is designed using PNN. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. We discuss two kinds of SONFN architectures and propose a comprehensive learning algorithm. It is shown that this network...

• 한국에너지공학회:학술대회논문집
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• 한국에너지공학회 1995년도 추계학술발표회 초록집
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• pp.75-81
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• 1995

DYLAM and its related applications are reviewed in detail and found to have many favourable characteristics. Concerning human factor analysis, the study demonstrates that DYLAM methodology represents an appropriate tool to study man-machine behaviour provided that DYLAM is used to model machine behaviour and an appropriate operator interface human factor model is included. A hybrid model which is a synthesis of the DYLAM model, a system thermodynamic simulation model and a neural network predicative model, is implemented and used to analyse dynamically the CANDU pressurizer system.

• 한국산업정보학회논문지
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• 제1권1호
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• pp.63-85
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• 1996

This paper describes the applications of genetic algorithm to nonlinear constrained optimization problems. Genetic algorithms are combinatorial in nature, and therefore are computationally suitable for treating continuous and idstrete integer design variables. For several problems , the conventional genetic algorithms are ill-defined , which comes from the application of penalty function , encoding and decoding methods, fitness scaling, and premature convergence of solution. Thus, we develope a hybrid genetic algorithm to resolve these problems and present two examples to demonstrate the effectiveness of the methodology developed in this paper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2702-2704
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• 2001

In this Letter, we propose a comprehensive design methodology of hybri'd Fuzzy controllers (HFC). The HFC comes as a form of a convex combination of a standard PID controller and a fuzzy controller. The design procedure dwells on the use of evolutionary computing (genetic algorithm) and an auto-tuning algorithm. The tuning of the scaling factors of the HFC is an essential component of the entire optimization process. A numerical study is presented and a detailed comparative analysis is also included.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1100-1106
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• 2009

General contractors' overhead costs are increasing relative to direct costs. However, it is difficult to apply the traditional activity-based costing directly to the construction site overhead costing because the resource consumption rate per each activity is varied depending on the attributes of activities. The research develops a methodology of hybrid cost allocation system when resources are assigned to cost objects unlike the traditional activity-based costing. The study also develops a database program and demonstrates how it can be applied to the construction projects using a case study.

• 융합보안논문지
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• 제15권4호
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• pp.43-55
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• 2015

ICT가 사회 주요 기반 구조로 자리매김 함에 따라 사이버 역량 강화 필요성이 대두되고 있다. 그러나 국내에 효과적인 사이버 역량 평가 방법론이 존재하지 않아 우리나라의 사이버 역량을 평가하고, 이에 기반한 역량 강화 방안 마련이 어려운 실정이다. 사이버 역량 평가는 우리의 사이버 역량 실태를 점검하여 정책 방향 수립에 활용하고 효과적인 예산 편성을 위한 근간을 제공할 수 있다. 그러나 현실적으로 사이버 역량 평가 항목이 다양하고, 각 항목의 판단 척도가 상이하여 의사 결정자가 판단하는데 어려움이 존재한다. 이에 본 논문에서는 AHP와 TOPSIS를 융합한 사이버 역량 평가 방법론을 제안하였다. AHP는 다양한 평가 항목간의 중요도 판별에 활용하고, TOPSIS는 평가 대상국 간의 순위 판별에 활용하였고, 가상 실험 데이터를 이용하여 주요 4개국에 대한 평가를 수행하였다. 실험 결과 제안한 사이버 평가 방법론은 AHP를 이용한 사이버 평가에 비해 평가 항목과 평가 대상국의 확장이 가능하고, 보다 정교한 수학적 기반을 통해 객관적인 평가가 가능한 것으로 나타났다.

• Nuclear Engineering and Technology
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• 제50권3호
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• pp.396-410
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• 2018

To assist operators to properly assess the current situation of the plant, accurate fault diagnosis methodology should be available and used. A reliable fault diagnosis method is beneficial for the safety of nuclear power plants. The major idea proposed in this work is integrating the merits of different fault diagnosis methodologies to offset their obvious disadvantages and enhance the accuracy and credibility of on-line fault diagnosis. This methodology uses the principle component analysis-based model and multi-flow model to diagnose fault type. To ensure the accuracy of results from the multi-flow model, a mechanical simulation model is implemented to do the quantitative calculation. More significantly, mechanism simulation is implemented to provide training data with fault signatures. Furthermore, one of the distance formulas in similarity measurement-Mahalanobis distance-is applied for on-line failure degree evaluation. The performance of this methodology was evaluated by applying it to the reactor coolant system of a pressurized water reactor. The results of simulation analysis show the effectiveness and accuracy of this methodology, leading to better confidence of it being integrated as a part of the computerized operator support system to assist operators in decision-making.

• International Journal of Control, Automation, and Systems
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• 제3권2호
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• pp.183-194
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• 2005

In this study, we introduce an advanced architecture of genetically optimized Hybrid Fuzzy Neural Networks (gHFNN) and develop a comprehensive design methodology supporting their construction. A series of numeric experiments is included to illustrate the performance of the networks. The construction of gHFNN exploits fundamental technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms (GAs). The architecture of the gHFNNs results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). In this tandem, a FNN supports the formation of the premise part of the rule-based structure of the gHFNN. The consequence part of the gHFNN is designed using PNNs. We distinguish between two types of the linear fuzzy inference rule-based FNN structures showing how this taxonomy depends upon the type of a fuzzy partition of input variables. As to the consequence part of the gHFNN, the development of the PNN dwells on two general optimization mechanisms: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gHFNN, the models are experimented with a representative numerical example. A comparative analysis demonstrates that the proposed gHFNN come with higher accuracy as well as superb predictive capabilities when comparing with other neurofuzzy models.

• 정보처리학회논문지D
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• 제8D권3호
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• pp.233-240
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• 2001

소프트웨어 개발 기술이 발전하고 소프트웨어 정량화의 중요성이 커지면서 많은 메트릭들이 여러 시스템 개체의 정량화를 위해 제안되었다. 이들은 크게 스칼라 메트릭 형태나 벡터 형태를 취한다. 최근에 몇몇 연구들에서 스칼라 메트릭의 조합 형태에서 오는 위험성을 지적하였지만 아직도 유용성 등의 큰 이점 때문에 많은 스칼라 메트릭들이 사용되고 있다. 본 논문은 기존 메트릭 연구들의 분석 과정을 통해 스칼라 메트릭 형태는 외부 복잡도에 가중을 둔 혼성 메트릭 형태가 가장 적당하다는 결론을 얻었으며 이를 토대로 개발 방법론과 개발 시스템 형태에 의존하지 않는 일반적인 혼성 복잡도 메트릭 제작 프레임워크를 제안한다. 제안 프레임워크는 구조적 방법론의 분석 단계와 객체지향 실시간 시스템 설계 단계의 정량화 프로젝트에 사용되었으며 두 프로젝트 모두 만족할만한 결과를 얻었다. 정량화 목적을 갖는 개발 집단은 제안 프레임워크를 이용하여 단시간 내에 여러 종류의 시스템 개체를 정량화할 수 있다.