• Journal of Navigation and Port Research
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• v.37 no.5
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• pp.493-498
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• 2013

This paper is aimed to priority evaluation of preliminary cases for IMO -IMS(International Maritime Organization- Information Management System) using fuzzy TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) and AHP(Analytic Hierarchy Process). To this solve, therefore, this paper extract 24 preliminary cases and select 4 major preliminary alternative cases after analysing the structure of its alternative cases using FSM(Fuzzy Structure Modeling). Also, the weights of evaluation factors determine using AHP which able to keep the consistency when decision-makers assess. In AHP method, but, the numbers of paired comparison incerase as much as the numbers of the comparison items increase and because this evaluation have the many of vagueness, the decision of final ranking is used to fuzzy TOPSIS method which is included TOPSIS and Fuzzy Set Theory. The result are developed as order as Management of IMO Convention Information, Delivery of IMO Convention Information, Total IMO Database, Knowledge Hub of IMO Convention Information in IMO-IMS.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.7
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• pp.909-915
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• 2014

Terminal voltage of the Automatic Voltage Regulator(AVR) of brushless synchronous generator is generally being controlled by PID Control way in shore and ship field. However, in case of changeable large load on power system, PID control method is deficiency to respond output voltage with settling time. Hence, taking into consideration this situation, it is required new control method. In this thesis, we propose Fuzzy Logic Control(FLC) which has more optimal robust control way in order to respond varying values of terminal voltage to the brushless synchronous generator through simulation of MATLAB/SIMULINK and prove Fuzzy logic control more optimal compared with PID control.

• Journal of Agricultural Extension & Community Development
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• v.19 no.4
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• pp.799-831
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• 2012

This study was accomplished to support farmers who want to introduce Automatic Milking System. The methods of analysis is considered on it as investment analysis that NPV, ROV and FROV. As a classical investment analysis technique, NPV showed 142 thousand won on the every senarioes. On the other hands, The Real Option Analysis showed 153,826, 154,937 and 152,858 on the normal, optimistic and pessimistic senarioes respectively. it is considered as a investment analysis technique for strategic decision-making. But, it may have problem to evaluate present value of expected cash flows and expected costs by a single number. To solve those problems, this paper tried to evaluate Fuzzy Real Option Model which were jointed with a real option model and Fuzzy set model. The result of analysis showed, on respective senarioes, 153,515 to 161,489, 154,612 to 162,970, and 152,573 to 159,835 on the interval estimation. Thereby It is a more realistic in many cases.

• Journal of Navigation and Port Research
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• v.33 no.1
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• pp.43-50
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• 2009

Recently, many maritime accidents have been increased and the collisions due to human error are given a great deal of proportions out of them We develop the Real-time Collision Risk Monitoring System (CRMS) for the navigational officers to cope with the emergency situation promptly and thus to reduce the probability of casualty. In this study, the risk of collision and grounding is evaluated by two kinds of method. The first method is based on Fuzzy algorithm, which evaluates the risk of collision between traffic ships. The second method is based on Environmental Stress (ES) Model, where the total risk of collision and grounding is evaluated by the environmental stress felt by human. The developed real-time CRMS has been installed to the ship handling simulator system and its capabilities have been tested through simulator experiments.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.357-365
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• 2022

Refrigerant mischarging is one of the most frequently occurring failure modes in air conditioners, and both undercharging and overcharging degrade cooling performance. Therefore, it is important to accurately determine the amount of charged refrigerant. In this study, a support vector machine (SVM) model was developed to multi-classify the refrigerant mischarge through steady-state identification via fuzzy clustering techniques. For steady-state identification, a fuzzy clustering algorithm was applied to the air conditioner operation data using the difference between moving averages. The identification results using the proposed method were compared with those using existing steady-state determination techniques studied through the inversed Fisher's discriminant ratio (IFDR). Subsequently, the main features were selected using minimum redundancy maximum relevance (mRMR) considering the correlation among candidate features, and an SVM multi-classification model was devised using the derived features. The proposed method achieves satisfactory accuracy and robustness from test data collected in the new domain.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.135-145
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• 2024

At the 80th session of the MEPC, the IMO presented an enhanced GHG reduction strategy. The strategy is more specific and robust than the initial strategy presented at the 72nd session. The IMO aims to achieve 'Net Zero' GHG emissions from international shipping by 2050. In this study, a risk assessment was conducted for representative green fuels, namely. LNG, hydrogen, methanol, and ammonia. The fuzzy method was used to resolve the subjective ambiguity of results from the survey of the experts, and the positive and negative ef ects of the fuzziness were derived through the TOPSIS method. Finally, the closeness coefficients of the considered alternative fuels were determined using the Vertex method. As a result, methanol, LNG, hydrogen, and ammonia were preferred. This study suggests that the proposed approach can be used as a collective decision-making tool for selecting alternative fuels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.3A
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• pp.172-178
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• 2012

This paper studies the application of a fuzzy-ARTMAP (FAM) neural network to multi-user detector (MUD) for direct sequence (DS)-code division multiple access (CDMA) system. This method shows new solution for solving the problems, such as complexity and long training, which is found when implementing the previously developed neural-basis MUDs. The proposed FAM based MUD is fast and easy to train and includes capabilities not found in other neural network approaches; a small number of parameters, no requirements for the choice of initial weights, automatic increase of hidden units, no risk of getting trapped in local minima, and the capabilities of adding new data without retraining previously trained data. In simulation studies, binary signals were generated at random in a linear channel with Gaussian noise. The performance of FAM based MUD is compared with other neural net based MUDs in terms of the bit error rate.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2382-2386
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• 2003

The Global Positioning System(GPS) is a satellite based precise positioning system avaliable worldwide. The GPS have many error sources. The earth's ionosphere and atmosphere cause delays in the GPS signal that translate into position errors. Some errors can be factored out using mathematics and modeling. The configuration of the satellites in the sky can magnify other errors. The problem of accuracy on GPS measurement data can be meaningful. In this study, we propose the method for GPS positioning accuracy improvement. The FUZZY set theory on PDOP(Position Dilution of Precision) and SNR(Signal to Noise Ratio) provide improved for measured positioning data. The accuracy of positioning has been improved by selecting data from original using the FUZZY set theory on PDOP and SNR.

• Architectural research
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• v.12 no.2
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• pp.85-92
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• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.395-398
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• 1998

In this paper, a method for the improvement of learning speed and convergence rate was proposed applied it to physiological neural structure with the advantages of artificial neural networks and fuzzy theory to physiological neuron structure, To compare the proposed method with conventional the single layer perception algorithm, we applied these algorithms bit parity problem and pattern recognition containing noise. The simulation result indicated that our learning algorithm reduces the possibility of local minima more than the conventional single layer perception does. Furthermore we show that our learning algorithm guarantees the convergence.