• Journal of Power Electronics
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• v.15 no.4
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• pp.1119-1130
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• 2015

This study investigates the multi-objective fuzzy optimization of crowbar resistance for the doubly fed induction generator (DFIG) low-voltage ride-through (LVRT). By integrating the crowbar resistance of the crowbar circuit as a decision variable, a multi-objective model for crowbar resistance value optimization has been established to minimize rotor overcurrent and to simultaneously reduce the DFIG reactive power absorbed from the grid during the process of LVRT. A multi-objective genetic algorithm (MOGA) is applied to solve this optimization problem. In the proposed GA, the value of the crowbar resistance is represented by floating-point numbers in the GA population. The MOGA emphasizes the non-dominated solutions and simultaneously maintains diversity in the non-dominated solutions. A fuzzy-set-theory-based is employed to obtain the best solution. The proposed approach has been evaluated on a 3 MW DFIG LVRT. Simulation results show the effectiveness of the proposed approach for solving the crowbar resistance multi-objective optimization problem in the DFIG LVRT.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.4
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• pp.304-309
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• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• ETRI Journal
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• v.24 no.4
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• pp.323-327
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• 2002

In this study, we propose a novel mobile tracking method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters-the received signal strength, the distance between the mobile and the base station, the moving direction, and the previous location-are used in the decision process using the aggregation function in the fuzzy set theory. Through numerical results, we show that our proposed mobile tracking method provides a better performance than the conventional method using the received signal strength.

• Honam Mathematical Journal
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• v.31 no.3
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• pp.335-349
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• 2009

Soft set theory by Molodtsov is applied to ideals in BCC-algebras. The notion of soft BCC-ideals of soft BCC-algebras and idealistic soft BCC-algebras are introduced, and several examples are provided. Relations between a fuzzy BCC-ideal and an idealistic soft BCC-algebra are given, and the characterization of idealistic soft BCC-algebras is established.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.197-200
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• 1991

In this paper, a technique to reduce the computational effort of Hough Transform used to recognize digital circles is proposed. The technique, which is a version of the Hough Transform uses bisectors of circles cords to estimate the center of circles. This system which is implemented in this paper gets center, radius, thickness of circular fiducials regardless of input form. This system uses fuzzy set theory which deals with 'ambigousness', In order to recognize imprecise circular fiducial.

• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.13-23
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• 1994

This study proposed a method of accessment for traffic flow on roads based on the driver's decision making. In order to, an attempt is carried out to express driving speeds through driver's congnitive language theoretically and experimentally. Membership function is derived to express driver's congnitive language about driving speed through a fuzzy set theory and examines the applicability for speed evaluation. As a resul, the membership function of the recognized as medium by drivers almost agrees with the frequency distribution of speeds on roads constrtained at 50km/h.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.3-6
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• 2000

In this paper, ‘gesture’ is discussed as a means of human-friendly communication between man and machine. We classify various gestures into two Categories: ‘contact based’ and ‘non-contact based’ Each method is reviewed and some real applications are introduced. Also, key design issues of the method are addressed and some contributions of soft-computing techniques, such as fuzzy logic, artificial neural networks (ANN), rough set theory and evolutionary computation, are discussed.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1072-1079
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• 2003

This study is purported for suggesting a new clustering algorithm that enables incremental categorization of numerous documents. The suggested algorithm adopts the natures of the spherical k-means algorithm, which clusters a mass amount of high-dimensional documents, and the fuzzy ART(adaptive resonance theory) neural network, which performs clustering incrementally. In short, the suggested algorithm is a combination of the spherical k-means vector space model and concept vector and fuzzy ART vigilance parameter. The new algorithm not only supports incremental clustering and automatically sets the appropriate number of clusters, but also solves the current problems of overfitting caused by outlier and noise. Additionally, concerning the objective function value, which measures the cluster's coherence that is used to evaluate the quality of produced clusters, tests on the CLASSIC3 data set showed that the newly suggested algorithm works better than the spherical k-means by 8.04% in average.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.144-156
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• 2023

Smart agriculture is a rapidly growing field that seeks to optimize crop yields and reduce risk through the use of advanced technology. A key challenge in this field is the need to create a comprehensive smart farm system that can effectively monitor and control the growth environment of crops, particularly when cultivating new varieties. This is where fuzzy theory comes in, enabling the collection and analysis of external environmental factors to generate a rule-based system that considers the specific needs of each crop variety. By doing so, the system can easily set the optimal growth environment, reducing trial and error and the user's risk burden. This is in contrast to existing systems where parameters need to be changed for each breed and various factors considered. Additionally, the type of house used affects the environmental control factors for crops, making it necessary to adapt the system accordingly. While developing such a framework requires a significant investment of labour and time, the benefits are numerous and can lead to increased productivity and profitability in the field of smart agriculture. We developed an AI platform for optimal control of facility houses by integrating data from mushroom crops and environmental factors, and analysing the correlation between optimal control conditions and yield. Our experiments demonstrated significant performance improvement compared to the existing system.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.312-316
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• 2010

현재 국내에서 주로 사용되고 있는 홍수기 다목적 댐의 홍수조절효과에 대한 정량적인 평가지표로는 유량조절률, 저수지 방류율, 저수지 저류율, 저수지 이용률 등이 있다. 이러한 평가지표들은 유입량, 방류량, 저류량 등의 자료를 단순 비교하는 방법을 사용하고 있는데, 홍수조절효과 평가지표 산정식에 사용되는 자료들이 가지는 불확실성이 평가에 고려되지 못하고 있으며, 다목적댐에서 얻을 수 있는 자료만을 사용함으로써 댐 하류 지점에서의 홍수조절효과를 평가하지 못하고 있다. 또한 수자원 시스템의 설계에 있어서 허용 가능한 부분적인 실패를 고려하지 못하는 등의 문제점이 존재하므로, 홍수조절효과를 정량화 할 수 있는 새로운 지표의 개발이 요구된다. 본 연구에서는 각종 변수들이 가지는 불확실성, 댐 하류지점에서의 홍수조절효과, 수자원 시스템에서 허용 가능한 부분적 실패를 고려하기 위하여 홍수조절효과 정량화 지표 개발에 퍼지집합 이론을 적용하였고, 충주댐 유역을 시험 유역으로 선정하여 연구를 수행하였다. 대상 홍수사상으로는 2006년도 7월의 홍수사상을 적용하였으며 그에 따른 인자들을 퍼지화하고 시스템의 상태로부터 허용 가능한 부분적인 실패 영역을 구분하였고, 통합 신뢰도-취약도 지수를 적용하여 홍수조절효과 정량화 지표를 개발하였다. 적용 결과, 본 연구를 통하여 개발된 통합 신뢰도-취약도 지수는 저수지의 홍수조절효과를 보다 구체적이고 객관화하여 나타낼 수 있었다.