• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.4
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• pp.194-199
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• 2017

Power transformers are an important factor for power transmission and cause fatal losses if faults occur. Various diagnostic methods have been applied to predict the failure and to identify the cause of the failure. Typical diagnostic methods include the IEC diagnostic method, the Duval diagnostic method, the Rogers diagnostic method, and the Doernenburg diagnostic method using the ratio of the main gas. However, each diagnostic method has a disadvantage in that it can't diagnose the state of the power transformer unless the gas ratio is within the defined range. In order to solve these problems, we propose a diagnosis method using ELM based intelligent algorithm and fuzzy membership function. The final diagnosis is performed by multiplying the result of diagnosis in the four diagnostic methods (IEC, Duval, Rogers, and Doernenburg) by the fuzzy membership values. To show its effectiveness, the proposed fault diagnostic system has been intensively tested with the dissolved gases acquired from various power transformers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.189-196
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• 1999

Until now, Many approach to use the layer or attribute items in GIS the classification results of remotely sensed images is going on, but It was rarely ever tried to use the results of fuzzy classification in GIS. The fuzzy classification can be accurate than any other classification methods of remotely sensed images and can separately extract the result for each classification items. In this study, We applied to GIS database implementation with fuzzy classification result. In the process of this study, We convert the fuzzy classification image into the grid of GIS database, and Membership Grade Value files transformed to table database into the GIS. And then Membership Grade Values related to each grid-cell of database be able to verify with pointer layer. Finally, we can use the fuzzy classification images in GIS database.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.7277-7282
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• 2014

In this study, the gradient descent algorithm was used for FLC analysis and the algorithm was used to represent the effects of nonlinear parameters, which alter the antecedent and consequence fuzzy variables of FLC. The controller parameters choose the control variable by iteration for gradient descent algorithm. The FLC consists of 7 membership functions, 49 rules and a two inputs - one output system. The system adopted the Min-Max inference method and triangle type membership function with a 13 quantization level.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.4
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• pp.363-369
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• 2002

In this paper, it could improved on the arbitrary nonlinear function learning approximation which have the wavelet neural network based on Adaptive Neuro-Fuzzy Inference System(ANFIS) and the multi-resolution Analysis(MRA) of the wavelet transform. ANFIS structure is composed of a bell type fuzzy membership function, and the wavelet neural network structure become composed of the forward algorithm and the backpropagation neural network algorithm. This wavelet composition has a single size, and it is used the backpropagation algorithm for learning of the wavelet neural network based on ANFIS. It is confirmed to be improved the wavelet base number decrease and the convergence speed performances of the wavelet neural network based on ANFIS Model which is using the wavelet translation parameter learning and bell type membership function of ANFIS than the conventional algorithm from 1 dimension and 2 dimension functions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.3
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• pp.676-683
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• 2005

In this paper, we proposed a method that optimal values of fuzzy control rule base and quantization of membership function are searched by genetic algorithm. Proposed method searched the optimal values of membership function and control rules using genetic algorithm by off-line. Then fuzzy controller operates using these values by on-line. Proposed fuzzy control system is optimized the control rule base and membership function by genetic algorithm without expert's knowledge. We investigated proposed method through simulation and experiment using DC motor and one link manipulator, and confirmed the following usefulness.

• Journal of Distribution Science
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• v.17 no.9
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• pp.25-33
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• 2019

Purpose - The purpose of the study was to seek to find out what factors having differences between paid membership customers (Costco membership) and general customers in retail industry. Since Costco operates differently from other conventional retailers, which is expected to have a substantial impact on consumers' preference of retail stores. Research design, data, and methodology - The survey conducted covered 1,000 adults in their 30s~50s living in Goyang and Gwangmyeong where Costco runs stores to determine the effects of Costco's local market-entry from consumer perspectives. 500 respondents were surveyed in each region and those working in the retail sector were excluded to ensure the objectivity of the answers. Results - Costco members in Goyang considered the price, bulk purchasing, and membership benefits as important criteria when choosing their retail store. On the other hand, as for Gwangmyeong, the non-member group's prominent characteristic was that they considered accessibility including travel distance and location and in-store amenities including food court services as important criteria for decision-making. Conclusion - Unique business model of Costco shows a statistically significant difference in terms of consumer awareness. the feature of Costco served as an critical criteria for consumers in their purchasing decision. Moreover, Bulk packaging purchases at Costco results in a strong supplementary relationship with neighborhood supermarkets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2231-2252
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• 2012

With the prevalence of diverse services-oriented applications, such as IPTV systems and on-line games, the current underlying communication networks face more and more challenges on the aspects of flexibility and adaptability. Therefore, an effective and efficient multicast routing mechanism, which can fulfill different requirements of different personalized services, is critical and significant. In this paper, we first define the neighbor gradient, which is calculated based on the weighted sum of attributes such as residual link capacity, normalized hop count, etc. Then two distributed multicast routing algorithms which are neighbor Gradient-based Multicast Routing for Static multicast membership (GMR-S) and neighbor Gradient-based Multicast Routing for Dynamic multicast membership (GMR-D), are proposed. GMR-S is suitable for static membership situation, while GMR-D can be used for the dynamic membership network environment. Experimental results demonstrate the effectiveness and efficiency of our proposed methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.722-728
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• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.138-147
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• 1993

It is known that the performance of a fuzzy controller is related with fuzzification method, inference rules, defuzzification method, and linguistic variables. Among these, generally, the linguistic variables and control rules are transfered to control engineers from an expert or experts of the controlled system and other parts are designed by control engineers. However, there may be some missed infirmations or uncertainties in the transfered data. The purpose of the paper is to propose an algorithm to tune the membership functions of initially given fuzzy sets To do so, a simple shape of the membership fuction is assumed for the fuzzy sets, and the relations between the shapes of the fuzzy sets and the performance of the control system is derived. According to the relations, the shape of the membership functions are modified during operation of the whole system. The proposed algorithm will be applied to two emample plants, type 1 and type 0 systems.

• Journal of the Ergonomics Society of Korea
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• v.23 no.1
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• pp.1-12
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• 2004

The purpose of this study was to develop an automatic expert system for the evaluation of human sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was also to develop an algorithm in which human arousal and pleasant level can be judged by using measured physiological signals. Fuzzy theory was applied for mathematical handling of the ambiguity related to evaluation of human sensibility. and the degree of belonging to a certain sensibility dimension was quantified by membership function through which the sensibility evaluation was able to be done. Determining membership function was achieved using results from a physiological signal database of arousal/relaxation and pleasant/unpleasant that was generated from imagination. To induce one final result (arousal and pleasant level) based on measuring the results of more than 2 physiological signals and the membership function of each physiological signal. Dempster-Shafer's rule of combination in evidence was applied, through which the final arousal and pleasant level was inferred.