• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.75-76
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• 2007

A mis-handling of the ship operators show high rate among the whole marine accidents. Since the port conditions have been getting worse. also as her size and speed increase, collision risk has been increased so that ship needs the automatic control system for collision. From that purpose, this research has been proceeded. The research has based on the MMG mathematical model, used Surge-Sway-Yaw motion equation, the information from the position and estimated time of collision point (DCPA and TCPA) to determine the collision risk with Fuzzy theory. To verify this system, ship was simulated when the ship encountered multitude of ships around the coast. The simulation result shows good application in avoiding ship collisions around the coast.

• Korean Journal of Construction Engineering and Management
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• v.12 no.1
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• pp.62-72
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• 2011

Currently, The failure of construction project is increasing to be caused by a changing construction environment. According to this circumstances, Researches of project success factors affecting performance have been presented to develop strategies for efficient construction project management in the construction industry. However, Conducting efficient construction project management is difficult because project manager could not know which project success factors can be improved or not. Especially, although the project characteristics were derived the level of difficulty for performance, research of the project characteristics which could not be improved as influence factor to performance is lacking. Therefore, This paper has developed the Performance Predicting System(PPS) with Fuzzy set theory to establish. PPS has been developed to establish efficient project management strategies and to save time and effort. As Contractor inputs the project characteristics, PPS can predict the level of difficulty of performance.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4111-4124
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• 2022

The control rod drive system is critical to the reactor's reliable operation. The performance of its control system and mechanical system will gradually deteriorate because of operational and environmental stresses, thus increasing the reactor's operational risk. Currently there are few researches on the aging-related degradation of the entire control rod drive system. Because it is difficult to quantify the effect of various environmental stresses and establish an accurate physical model when multiple mechanisms superimposed in the degradation process. Therefore, this paper investigates the aging-related degradation of a control rod drive system by integrating Dynamic Object-Oriented Bayesian Network and Hidden Markov Model. Uncertainties in the degradation of the control system and mechanical system are addressed by using fuzzy theory and the Hidden Markov Model respectively. A system which consists of eight control rod drive mechanisms divided into two groups is used to demonstrate the method. The aging-related degradation of the control rod drive system is analyzed by the Bayesian inference algorithm based on the accelerated life test data, and the impact of different operating schemes on the system performance is also investigated. Meanwhile, the components or units that have major impact on the system's performance are identified at different operational phases. Finally, several essential safety measures are suggested to mitigate the risk caused by the system degradation.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.490-495
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• 1999

In this paper, a method of improving the learning time and convergence rate is proposed to exploit the advantages of artificial neural networks and fuzzy theory to neuron structure. This method is applied to the XOR Problem, n bit parity problem which is used as the benchmark in neural network structure, and recognition of digit image in the vehicle plate image for practical image application. As a result of the experiments, it does not always guarantee the convergence. However, the network showed improved the teaming time and has the high convergence rate. The proposed network can be extended to an arbitrary layer Though a single layer structure Is considered, the proposed method has a capability of high speed 3earning even on large images.

• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.99-106
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• 1991

For the automatic detection of pulmonary blood vessels, a new algorithm is proposed using the fact that human recognizes a pattern orderly according to their size. This method simulates the human recognition process by the pyramid images. For the detection of vessels using multilevel image, large and wtde ones are detected from the most compressed level, followed by the detection of small and narrow ones from the less compressed images with FCM(fuzzy c means) clustering algorithm which classifies similar data into a group. As the proposed algorithm detects blood vessels orderly according to their size, there is no need to consider the variation of parameters and the branch points which should be considered in other detection algirithms. In the detection of patterns whose size changes successively like pulmonary blood vessels, this proposed algorithm can be properly applied

• Journal of the Korean Institute of Gas
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• v.21 no.2
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• pp.58-63
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• 2017

Currently, the safety monitoring process in a complex plant environment is proceeded by human. Sometimes, human error that may occur in a filed causes an severe problem. This paper introduces new method of safety monitoring system using sound information and fuzzy theory that is one of intelligent theories, in order to recognize the status of plant environment. In this paper, the filling station of high pressure gas will be used as a test plant. The result system will be widely applied for more complex plant environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.920-926
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• 2004

The human being receives a new information from outside and the information shows gradual oblivion with time. But the information remains in memory and isn't forgotten for a long time if the information is read several times over. For example, we assume that we memorize a telephone number when we listen and never remind we may forget it soon, but we commit to memory long time by repeating. If the human being received new information with strong stimulus, it could remain in memory without recalling repeatedly. The moments of almost losing one's life in an accident or getting a stroke of luck are rarely forgiven. The human being can keep memory for a long time in spite of the limit of memory for the mechanism mentioned above. In this paper, we propose a model to explain the mechanism mentioned above using a neural network and fuzzy.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.467-472
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• 2002

In this paper, we propose a Fuzzy Cellular Neural Network(FCNN) that is based on a-Least Trimmed Square Hausdorff distance(a-LTSHD) which applies Hausdorff distance(HD) to the FCNN structure in order to remove the impulse noise of images effectively and also improve the speed of operation. FCNN incorporates Fuzzy set theory to Cellular Neural Network(CNN) structure and HD is used as a scale which computes the distance between set or two pixels in binary images without confrontation of the feature object. This method has been widely used with the adjustment of the object. For performance evaluation, our proposed method is analyzed in comparison with the conventional FCNN, with the Opening-Closing(OC) method, and the LTSHD based FCNN by using Mean Square Error(MSE) and Signal to Noise Ratio(SNR). As a result, the performance of our proposed network structure is found to be superior to the other algorithms in the removal of impulse noise.

• Journal of Navigation and Port Research
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• v.41 no.1
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• pp.9-16
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• 2017

The maritime industry is recognized as an important national industry in the world today, and its importance is increasing. One of the most important marine industries is the marine leisure industry. Korea attracts many foreign visitors, and a wide variety of cultural and tourist resources are worth accessing. Among the visitors are Chinese tourists, who are called Youke and who represent a constantly increasing trend since 2007, when 1.06 million people visited, to 2015, when 5.98 million people visited Accordingly, a budget of about one trillion won has been committed to creating a resort complex called Golden Harbor at Incheon, which will focus on the development of a marine tourism complex In this study, we conduct a survey on the potential of Chinese tourism and marine tourism professionals only success of the targets of the Incheon Port Authority was analyzed by comparing the difference. A fuzzy analysis of the questionnaire results on Chinese tourists showed the importance of giving the highest priority to services being friendly(0.823), followed by safety(0.823) and convenience(0.773), highlighting the importance of recognize a variety of tourism products(0.755). Targeted surveys were conducted on 20 of Incheon Port Authority s employees They showed that various tourism products are the main issue(0.852), following by accessibility(0.850) and immigration(0.810), showed that convenience is important to recognize the order of (0.793).

• Journal of Power Electronics
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• v.15 no.5
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• pp.1274-1285
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• 2015

This paper deals with model reference adaptive system (MRAS) speed estimators based on a secondary flux for linear induction motors (LIMs). The operation of these estimators significantly depends on an adaptation mechanism. Fixed-gain PI controller is the most common adaptation mechanism that may fail to estimate the speed correctly in different conditions, such as variation in machine parameters and noisy environment. Two adaptation mechanisms are proposed to improve LIM drive system performance, particularly at very low speed. The first adaptation mechanism is based on fuzzy theory, and the second is obtained from an LIM mechanical model. Compared with a conventional PI controller, the proposed adaptation mechanisms have low sensitivity to both variations of machine parameters and noise. The optimum parameters of adaptation mechanisms are tuned using an offline method through chaotic optimization algorithm (COA) because no design criterion is given to provide these values. The efficiency of MRAS speed estimator is validated by both numerical simulation and real-time hardware-in-the-loop (HIL) implementations. Results indicate that the proposed adaptation mechanisms improve performance of MRAS speed estimator.