• 한국전자파학회논문지
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• 제21권7호
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• pp.715-725
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• 2010

OFDM(Orthogonal Frequency Division Multiplexing) 시스템은 주파수 선택적 페이딩 채널에서 무선 고속 데이터 전송에 적합한 통신 방식이다. 본 논문에서는 기계 제어에 많이 사용되는 Fuzzy 이론을 이용하여 OFDM 시스템에서 문제가 되는 PAPR(Peak to Average Power Ratio)을 감소시키는 방법을 제안한다. PAPR을 줄이는데 Fuzzy 이론을 사용함으로써 경험적 실험과 반복에 의한 데이터를 사용하기 쉬우며, 하드웨어적인 측면에서 구현이 쉽고, 또한 보다 적은 연산량으로 쉽게 PAPR을 감소시킬 수 있다. 먼저 입력 신호를 부블록으로 나누고, Fuzzy를 이용하여 부블록의 PAPR을 낮추어 전체의 PAPR을 낮추어 전송하여 이를 수신단에서 복원하는 비교적 쉽고 간단한 알고리즘을 제안한다. 제안한 방식이 기존의 OFDM 시스템에 비하여 시스템의 연산량이 다소 증가하고 Fuzzy에 관한 정보를 따로 보내야 하는 단점이 있지만, PAPR 감소 측면에서 성능이 개선됨을 확인하였다. 제안하는 알고리즘의 성능을 평가하기 위해 CCDF(Complementary Cumulative Distribution Function)을 통하여 비교한다. 이 알고리즘에 따르면 QPSK와 16QAM 변조를 사용하여 시뮬레이션을 한 결과, Fuzzy 이론을 이용한 방법이 FFT 크기(N)=512, Oversampling=4인 경우 PR이 $10^{-5}$을 기준으로 각각 최대 약 2.3 dB와 3.1 dB의 PAPR 감소됨을 확인할 수 있었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.310-313
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor (IPMSM) drive New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzy clear out integrated quantities according to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for IPMSM drive system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.1100-1102
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• 2000

Most systems in tile real world are non-linear and can be represented by the non-linear autoregressive moving average (NARMA) model. The extension of fuzzy system for modeling the system that is represented by NARMA model will be proposed in this paper. Here, fuzzy basis function (FBF) is used as fuzzy NARMA(p,q) model. Then, an approach to Identify fuzzy NARMA models based on fuzzy basis functions is proposed. The efficacy of the proposed approach is shown from experimental results.

• 한국지반공학회논문집
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• 제16권6호
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• pp.127-139
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• 2000

In the study, an expert system was developed to predict the safety of tunnel and select proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database, For this development, many tunnelling sites were investigated and the applied countermeasures were studied after building tunnel database. There will be benefit for the deciding tunnel reinforcement method in the case of poor ground condition. The expert system developed in the study has two main parts, pre-module and post-module. Pre-module is used to decide input items of tunnel information based on the tunnel face mapping information which can be easily obtained in in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. Post-module is used to infer the applicability of each reinforcement methods according to the face level. The result of the predicted reinforcement system level was similar to measured ones. In-situ data were obtained in three tunnel sites including subway tunnel under Han River. Therefore, this system will be helpful to make the mose of in-situ data available and suggest proper applicability of tunnel reinforcement system to development more resonable tunnel support method without dependance of some experienced experts opinions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.171-177
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• 2011

The decision making process is based on accurate and timely available information. To obtain precise information from the internet is becoming more difficult due to the continuous increase in vagueness and uncertainty from online information resources. This also poses a problem for blind people who desire the full use from online resources available to other users for decision making in their daily life. Ontology is considered as one of the emerging technology of knowledge representation and information sharing today. Fuzzy logic is a very popular technique of artificial intelligence which deals with imprecision and uncertainty. The classical ontology can deal ideally with crisp data but cannot give sufficient support to handle the imprecise data or information. In this paper, we incorporate fuzzy logic with heavyweight ontology to solve the imprecise information extraction problem from heterogeneous misty sources. Fuzzy ontology consists of fuzzy rules, fuzzy classes and their properties with axioms. We use Fuzzy OWL plug-in of Protege to model the fuzzy ontology. A prototype is developed which is based on OWL-2 (Web Ontology Language-2), PAL (Protege Axiom Language), and fuzzy logic in order to examine the effectiveness of the proposed system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.897-900
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• 1998

Through fuzzy logic controller is very useful to many areas, it is difficult to build up the rule-base by experience and trial-error. So, effective self-tuning fuzzy controller for the position control of ball and beam is designed. In this paper, we developed the neural network control system with fuzzy-neuron which conducts the adjustment process for the parameters to satisfy have nonlinear property of the ball and beam system. The proposed algorithm is based on a fuzzy logic control system using a neural network learinign algorithm which is a back-propagation algorithm. This system learn membership functions with input variables. The purpose of the design is to control the position of the ball along the track by manipulating the angualr position of the serve. As a result, it is concluded that the neural network control system with fuzzy-neuron is more effective than the conventional fuzzy system.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.359-362
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• 2003

In PDP(Plasma Display Panel), sub-field method is used to implement gray scale. Each sub-field has different periods. And Every gray level has information of which sub-field has to be displayed. This is called sub-field mapping. There are several sub-field mapping values in some gray levels. So, it is possible to select best choice in this paper, we propose new sub field mapping method using a fuzzy inference system to select best sub-field mapping values in accordance with input image and environment temperature. In order to implement fuzzy system, we used MATLAB fuzzy inference editor.

• 대한산업공학회지
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• 제29권1호
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• pp.32-40
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• 2003

In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.2964-2983
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• 2015

As the Android operating system has become a key target for malware authors, Android protection has become a thriving research area. Beside the proved importance of system permissions for malware analysis, there is a lot of overlapping in permissions between malware apps and goodware apps. The exploitation of them effectively in malware detection is still an open issue. In this paper, to investigate the feasibility of neuro-fuzzy techniques to Android protection based on system permissions, we introduce a self-adaptive neuro-fuzzy inference system to classify the Android apps into malware and goodware. According to the framework introduced, the most significant permissions that characterize optimally malware apps are identified using Information Gain Ratio method and encapsulated into patterns of features. The patterns of features data is used to train and test the system using stratified cross-validation methodologies. The experiments conducted conclude that the proposed classifier can be effective in Android protection. The results also underline that the neuro-fuzzy techniques are feasible to employ in the field.

• 한국수자원학회논문집
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• 제37권6호
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• pp.449-460
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• 2004

본 논문에서는 월 댐유입량을 예측하는데 있어서 기상예보정보를 활용한 뉴로-퍼지 시스템의 적용성을 검토하였다. 뉴로-퍼지 알고리즘으로 퍼지이론과 신경망이론의 결합형태인 ANFIS(Adaptive Neuro-Fuzzy Inference System)을 이용하여 모형을 구성하였다. ANFIS의 공간분할에 의한 제어규칙의 선정에 있어 퍼지변수가 증가함에 따라 제어규칙이 기하급수적으로 증가하는 단점을 해결하기 위해 퍼지 클러스터링(Fuzzy Clustering)방법 중 하나인 차감 클러스터링(Subtractive Clustering)을 사용하였다. 또한 본 연구에서는 정성적인 기상예보정보를 정량화 시키는 방법을 제안하였다. AMFIS를 이용하여 월 댐유입량 예측 시, 관측자료만으로 구성된 모형에 의한 예측결과와 관측자료에 기상예보정보를 더하여 구성된 모형에 의한 예측결과를 비교하였다. 그 결과 ANFIS는 기상예보정보를 활용하여 댐유입량을 예측했을 때가 관측자료만으로 예측했을 때보다 예측능력이 더욱 정확함을 보였다.