• 한국항공운항학회:학술대회논문집
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• 2006.11a
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• pp.167-172
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• 2006

본 연구에서는 AFTM이 필요한 이유를 항공기의 불확실성을 들어서 설명 하였다. 불확실성의 원인으로 수요, 수용량의 불확실성과 ATFM의 조정행동과 타이밍조정을 위한 불확실성에 근거하여 알아보았다. 이와 같은 불확실성을 줄이기 위한 방법으로는 정보 질의 향상과 다양한 가능성에 대한 문제를 예측하여 최적화하는 방법으로 해결할 수 있다. 슬롯교환메커니즘에서 가장 기본적인 알고리즘으로는 압축방법에 대하여 살펴보았고 항공사내에서 처리할 수 있는 항공사 슬룻 대체알고리즘을 설명하였다. 그러나 한 항공사에서 대체할 수 없는 경우에는 다른 항공사에서 대체 항공편을 제공하는 메커니즘에 대하여 알아보았다. 이어서 압축방법의 기본이론인 일괄처리방법과 SCS 의 신속대응메커니즘의 차이점과 장단점을 살펴보았다. 이어진 연구과제로 두 모델의 수학적 모델을 연구하여 그 특성을 파악하여 모델을 개발하여 시뮬레이션 하는 것이다. 더 나아가서는 메커니즘의 모범 예제라 할 수 있는 SCS 에서 실제적으로 어떻게 적용되고 있는지 사례에 대하여 연구하려 한다.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.31-37
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• 2000

지금까지 고장예측에 관한 연구 논문들은 여러 분야에서 많이 다루어져 왔다. 그 대표적인 예측 방법 중에 하나인 FTA(Fault Tree Analysis)가 가장 많이 사용되어져 왔으며, 여러 산업분야에서 가장 활발하게 시스템 및 부품에 대한 고장 가능성 진단을 실시하여 왔다. 하지만 기존의 전통적인 FTA 방법을 사용하는데 있어서 몇 가지 문제점을 발견할 수가 있었다. 즉, 지금까지 FTA를 실시하는 과정에 있어서 시스템 및 부품에 대한 데이터의 자료가 정확하다는 전제하에 고장 값을 예측하여 왔다. 만일 시스템 및 부품에 대한 불확실한 데이터나 부정확한 자료를 동시에 가지고 있다면 지금까지 사용하여 왔던 전통적인 FTA를 사용하여 고장 값을 예측하여 정확한 값을 찾아내기란 어려운 것이라 할 수가 있다. 이와 같은 문제점을 해결하기 위해서는 본 연구에서 제시하는 Fuzzy FTA를 사용하는 것이 보다 바람직할 것이며, 이러한 방법을 사용하여 불확실하고 부정확한 데이터를 가지고 고장진단을 실시하여 고장가능성 값을 찾아내어 전체 시스템의 고장 발생 가능성을 예측하는 것이 이 논문의 목적이라 할 수가 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.552-556
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• 2004

This paper surveys the design of the adaptive information filtering agents to retrieve the useful information within a large scale database. As the information retrieval through the Internet is generalized, it is necessary to extract the useful information satisfied the user's request condition to reduce the seeking time. For the first, this module is designed by the Rough reduct to generate the reduced minimal knowledge database considered the users natural query language in a large scale knowledge database, and also it is executed the soft computing by the fuzzy composite processing to operate the uncertain value of the reduced schema domain.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.441-452
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• 2002

If continuous moving objects are managed by conventional database, it is not possible for them to store all position information changed over time in the database. Therefore, a time period of regular rate is determined and position information of moving objects are discretely stored in the system for every time period. However, if continuous moving objects are managed as discrete model, we will have problems which cannot properly answer to the query about uncertain past or future position information. To solve this problem, in this paper, we propose the method and algorithm which use the history information stored in the same database, to estimate the past or future location of moving objects. The cubic spline interpolation is used to estimate the past location and the mean movement value of the history information is used to predict the future location of moving objects. Finally, from the location estimation experimentation of using virtual trajectory and location sample, we proved that the proposed cubic spline function has less error than the linear function.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.305-313
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• 2021

The upcoming warfare will be network-centric warfare with the acquiring and sharing of information on the battlefield through the connection of the entire weapon system. Therefore, the amount of information generated increases, but the technology of evaluating the information is insufficient. Threat assessment is a technology that supports a quick decision, but the information has many uncertainties and is difficult to apply to an advanced battlefield. This paper proposes a threat assessment based on artificial intelligence while removing the target uncertainty. The artificial intelligence system used was a fuzzy inference system and a multi-layer perceptron. The target was classified by inputting the unique characteristics of the target into the fuzzy inference system, and the classified target information was input into the multi-layer perceptron to calculate the appropriate threat value. The validity of the proposed technique was verified with the threat value calculated by inputting the uncertain target to the trained artificial neural network.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.17-30
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• 2003

The purpose of this study is to identify the relationships among information search activities, of which perceived risk, cognitive dissonance, and involvement play a role. A survey of 155 students who have a recent experience on information search activities. Total six hypotheses the research already reported on information search effort, thereby giving decision maker a richer understanding of information search behavior.

• Korean Journal of Remote Sensing
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• v.20 no.6
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• pp.383-396
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• 2004

The application of spatial statistics to obtain the spatial uncertainty distributions in classification of remote sensing images is investigated in this paper. Two quantitative methods are presented for describing two kinds of uncertainty; one related to class assignment and the other related to the connection of reference samples. Three quantitative indices are addressed for the first category of uncertainty. Geostatistical simulation is applied both to integrate the exhaustive classification results with the sparse reference samples and to obtain the spatial uncertainty or accuracy distributions connected to those reference samples. To illustrate the proposed methods and to discuss the operational issues, the experiment was done on a multi-sensor remote sensing data set for supervised land-cover classification. As an experimental result, the two quantitative methods presented in this paper could provide additional information for interpreting and evaluating the classification results and more experiments should be carried out for verifying the presented methods.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• 대한공업교육학회지
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• v.34 no.2
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• pp.396-410
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• 2009

The goal of this work is to present an advanced method of an estimation of the Modeling Uncertainties coming up in industrial rigid robot's manipulator and actuators. First, with the given physical robot model, the motion equation was derived. Considering a fictitious model, a new extended motion equation is developed. Based on this extended model, an observer and observer bank are designed for the estimation of modeling uncertainties which are involving the effects of gravity, friction, mass unbalance, and Coriolis which show the nonlinear characteristics in operation states.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.4
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• pp.359-371
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• 2001

Project scheduling under resource constraint conditions have contained to many uncertain factors and it is perfonned by human experts. The expert identifies the activities of the project, decides the precedent relationships between these activities, and then construct the schedule using expected activity's duration. At this time, most of the scheduling methods concentrate on one of scheduling factor between activity duration and cost. And the activity duration, which is the most important factor in scheduling, is decided by heuristic of expert. Therefore it may cause uncertainty of activity duration decision and the use of this activity duration may increase the uncertainty of constructed schedule. This paper proposes Fuzzy-MOEH scheduling algorithm, which is the aggregation of the fuzzy number for deciding activity duration and applies the cost function for solving the problems of previous scheduling methods. This paper also analyze the utility and property of Fuzzy-MEOH algorithm through the comparison between Fuzzy-MEOH algorithm and existing MEOH algorithm.