• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.413-420
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• 2005

In this paper, we apply software agents, which use fuzzy logic and make autonomous decisions according to state transitions, to car driving environment. We carry out an experiment on artificial intelligent car driving in terms of real-time reactive agents. Inference techniques for constructing real-time reactive agents consider the settings with max-product inference, n-fuzzy rules, and n-associatives ($A_l,\;B_l),\;{\ldots}(A_n,\;B_n$). Then we perform defuzzification processes, extract a central value, and work out inference processes.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.51-60
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• 2011

Authentication model in the wireless environment has many security vulnerabilities. However, there is no adapting standard method in this field. Therefore, we propose a fuzzy logic based authentication model to enhance the security level in the authentication environment. We use fuzzy logic based classification to construct our model, and also additionally utilize improved AHP and case-based reasoning for an appropriate decision making. We compute the context information by using the improved AHP method, use the proposed model to compute the security level for the input data, and securely apply the proposed model to the wireless environment which has diverse context information. We look forward to better security model including cloud computing by extending the proposed method in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.292-297
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• 2016

This paper presents a navigation problem for an autonomous mobile robot in an unknown environment. The environment contains various types of obstacles and is completely unknown to the robot. Therefore, all of the surrounding information must be detected by the robot's proximity sensors. A navigation method was developed based on a fuzzy inference system to guide the robot to move along a collision-free path and reach the goal position quickly. The obstacles are assumed to be static, and both regular and irregular types of obstacles were investigated. A wall following method is also proposed for a special environment that contains a labyrinth or sharp U-valley obstacles. Simulation results demonstrate that the proposed method has great potential for this navigation problem.

• Journal of the Korean Society of Marine Environment & Safety
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• v.12 no.2 s.25
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• pp.145-150
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• 2006

This paper proposes an analysis to image of Inchon port using fuzzy theory. After analysis, positive opinion is mean membership function 0.73 and positive membership function 0.27, negative opinion is mean membership function 0.69, negative membership function 0.31 about Inchon port development. therefore, for port development need to accomodation of each opinion positive opinion is maximum decrease from 20 age to 30 age. and negative opinion is maximum increase from 10 age to 20 age. According to the results, port development need to high positive image as leisure and development of waterfront and low negative image as integrated port management and strategy of considered environment port.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.79-84
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• 2005

This paper proposes an analysis to image of inchon port using fuzzy theory. After analysis, positive opinion is mean membership function 0.73 and positive membership function 0.27, negative opinion is mean membership function 0.69, negative membership function 0.31 about inchon port development. therefore, for port development need to accomodation of each opinion postive opinion is maximum decrease from 20 age to 30 age. and negative opinion is maximum increase from 10 age to 20 age. According to the results, port development need to high positive image and low negative image.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.180-185
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• 2003

This paper proposes an intelligent navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. The experiments which demonstrate the performance of the proposed intelligent controller is described.

• Advances in Computational Design
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• v.5 no.4
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• pp.445-465
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• 2020

This paper presents a study conducted with the aim of developing a model of tendering based on a technique of artificial intelligence by managing and controlling the factors of success or failure of construction projects through the evaluation of the process of invitation to tender. Aiming to solve this problem, analysis of the current environment based on SWOT (Strengths, Weaknesses, Opportunities, and Threats) is first carried out. Analysis was evaluated through a case study of the construction projects in Algeria, to bring about the internal and external factors which affect the process of invitation to tender related to the construction projects. This paper aims to develop a mean to identify threats-opportunities and strength-weaknesses related to the environment of various national construction projects, leading to the decision on whether to continue the project or not. Following a SWOT analysis, novel artificial intelligence models in forecasting the project status are proposed. The basic principal consists in interconnecting the different factors to model this phenomenon. An artificial neural network model is first proposed, followed by a model based on fuzzy logic. A third model resulting from the combination of the two previous ones is developed as a hybrid model. A simulation study is carried out to assess performance of the three models showing that the hybrid model is better suited in forecasting the construction project status than RNN (recurrent neural network) and FL (fuzzy logic) models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.90-100
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• 2015

This study is conducted to suggest ways to mitigate the mismatch phenomenon between job seekers who want to find right company for themselves and companies looking for appropriate new employees. For this purpose, this study improves the company assessment framework reflecting job seekers interests by using fuzzy analytic hierarchy process. The improved evaluation framework is a three-level hierarchical structure, where there are 4 groups at the top level, 12 factors at the intermediate level and 36 indexes at the bottom level. For the empirical analysis of the applicants preferences based on the improved model, a survey for F-AHP analysis is carried out to university students and then priorities of components in the evaluation model are calculated. Moreover, the differences of priority of the company assessment framework are analyzed for different genders, college years, and major divisions. The results show that job seekers' most concerning factors are wages, stability, working environments, and labor deal, which are ranked highly in this order and the differences in preferences for each type of job seekers (genders, college years, and major divisions) are obvious. The results also show that the male prefers wages to environment, on the other hand female does working environment to wages.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.541-551
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• 2020

Based on the trend, there have been numerous researches analysing the ship collision risk. However, in this scope, the navigational conditions and external environment are ignored or incompletely considered in training or/and real situation. It has been identified as a significant limitation in the navigational collision risk assessment. Therefore, a novel algorithm of the ship navigational collision risk solving system has been proposed based on basic collision risk and vulnerabilities of marine accidents. The vulnerability can increase the possibility of marine collision accidents. The factors of vulnerabilities including bad weather, tidal currents, accidents prone area, traffic congestion, operator fatigue and fishing boat operating area are involved in the fuzzy reasoning engines to evaluate the navigational conditions and environment. Fuzzy logic is employed to reason basic collision risk using Distance to Closest Point of Approach (DCPA) and Time of Closest Point of Approach (TCPA) and the degree of vulnerability in the specific coastal waterways. Analytical Hierarchy Process (AHP) method is used to obtain the integration of vulnerabilities. In this paper, vulnerability factors have been proposed to improve the collision risk assessment especially for non-SOLAS ships such as coastal operating ships and fishing vessels in practice. Simulation is implemented to validate the practicability of the designed navigational collision risk solving system.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1999.10a
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• pp.203-204
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• 1999

대기질의 통계예측모형은 주로 오존 농도 예측에 사용된다. 통계예측 방법은 중회귀 모형, 신경망 모형, Fuzzy 논리 모형 등이 있다. 중회귀 모형은 종래 통계분석 방법으로 예전부터 많이 사용되고 있는 방법인 반면에 신경망 모형과 Fuzzy 논리 모형은 최근에 개발되어 적용가능성을 검토 중인 방법이다. 국내외 연구결과에 의하면 각 방법에 의한 고농도 오존 예측성은 크게 다르지 않았다. 국내에서는 중회귀 모형과 신경망 모형이 적용되었는데, 상관계수는 0.6-0.7저도로 보고되었다.(중략)