• Structural Engineering and Mechanics
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• 제87권3호
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.664-667
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• 2003

We propose a frizzy traffic controller of Sugeno's fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It uses 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. In order to construct fuzzy traffic controller of Sugeno's fuzzy model we first 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. Next we make Mamdani's fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Lastly, 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 service level of the traffic light controllers by using the delay time. As a result of comparison, the fuzzy traffic controller of Sugeno's fuzzy model shows the best service level of them.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권6호
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• pp.784-791
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• 2004

본 논문에서는 퍼지논리에 기초한 Fisherface 얼굴인식 방법의 확장을 다룬다. Fisherface 얼굴인식 방법은 주성분 분석 기법만을 이용하는 경우에 비해 조명의 방향, 얼굴의 포즈, 감정과 같은 변동에 대해 민감하지 않은 장점을 가지고 있다. 그러나, Fisherface 방법을 포함한 얼굴인식의 다양한 방법들은 입력 벡터가 한 클래스에 할당되어질 때 그 클래스에서 소속의 정도를 0 또는 1로서 나타낸다. 따라서 이러한 방법들은 얼굴영상들이 조명이나 보는 각도로 인해 변형이 생기는 경우에 인식률이 저하되는 문제가 있다. 본 논문에서는 PCA에 의해 변환된 특징벡터에 퍼지 소속도를 할당하는 것으로, 퍼지 소속도는 퍼지 kNN(k-Nearest Neighbor)으로부터 얻어진다. 실험 결과 ORL, Yale 얼굴 데이타베이스에서 기존의 인식방법 보다 향상된 인식 성능을 보임을 알 수 있었다.

• 한국콘텐츠학회논문지
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• 제8권3호
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• pp.107-116
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• 2008

본 연구는 호텔멤버십 운영에서 텔레마케터의 고객지향성이 종업원(텔레마케터) 만족에 미치는 영향을 규명하고자 서울지역을 비롯한 5개 지역의 특급호텔에 근무하는 텔레마케터를 대상으로 하였다. 실증분석을 통해 고객지향성이 높을수록 종사원 만족이 높아지는 것으로 나타났다. 또한 서울지역과 타지역간의 고객지향성과 종업원 만족의 차이와 인구 통계적 특성을 배경변수로 차이를 검증하였다. 본 연구는 호텔멤버십 연구에서 아직 다루지 않았던 호텔 텔레마케터를 대상으로 처음으로 연구를 시도하였고 이를 고객지향성과 연결시켰다는데 그 의의가 있다.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.306-310
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권4호
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• pp.306-311
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• 2008

Fuzzy regression, a nonparametric method, can be quite useful in estimating the relationships among variables where the available data are very limited and imprecise. It can also serve as a sound methodology that can be applied to a variety of management and engineering problems where variables are interacting in an uncertain, qualitative, and fuzzy way. A close examination of the fuzzy regression algorithm reveals that the resulting possibility distribution of fuzzy parameters, which makes this technique attractive in a fuzzy environment, is dependent upon an h parameter value. The h value, which is between 0 and 1, is referred to as the degree of fit of the estimated fuzzy linear model to the given data, and is subjectively selected by a decision maker (DM) as an input to the model. The selection of a proper value of h is important in fuzzy regression, because it determines the range of the posibility ditributions of the fuzzy parameters. In this paper, we discuss the interdependent relationship among the h value, membership function shape, and the spreads of fuzzy parameters in fuzzy linear regression with fuzzy input-output using shape-preserving operations.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 춘계학술발표대회 논문집
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• pp.143-148
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• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.1-19
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• 1998

In this Kdynote address, two types of information granules are considered : (ⅰ) one for set assignments of a concept descriptor and (ⅱ) the other for truthood assignment to the concept description verifier. The first is, the process which specifies the assignment of an object to a clump, a class, a group, etc., and hence defines the set membership with a relational constraint. the second is the assignment of the degree of truthood or the membership specification of the abstract concept of truthood which specifies the " veristic" constraint associated with the concept descriptor. The combination of these two distinct assignments let us generate four set and logic theories. This then leads to the concern of normal forms and their derivation from truth tables for each of these theories. In this regard, some of the fundamental issues arising in this context are discussed and certain preliminary answers are provided in order to highlight the consequences of these theories.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.428-433
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• 1994

This investigates the feasibility of applying fuzzy ogic controllers to the motion tracking control of a direct drive robot manipulator to deal with highly nonlinear and time-varying dynamics associated with robot motion. A fuzzy logic controller with narrow shape of membership functions near zero and wide shape far away zero is analyzed. Simulation and experimental studies have been conducted for a 2 degree of freedom direct drive SCARA robot to evaluate control performances, Fuzzy logic controllers have shown control performances that are often better, or at least, as good as those of conventional PID controllers. Furthermore, the control performance of fuzzy logic controllers can be improved by selecting membership functions of narrow shapes near zero and wide shapes far away zero.

• 산업경영시스템학회지
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• 제17권32호
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• pp.7-16
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• 1994

In the existing deterministic network, the capacity of each arc has determined property. But actually, it may be a property which cannot be determined. Even though it should be determining, it contains many errors. In treating these kinds of problems, fuzzy theory is suitable. Recently, due to development the study on complicated and indefinited systems which contain fuzziness could be possible. This paper includes that the capacity of each arc and the goal quantity with nonnegative integer have the fuzziness. The object is to search the new mathod of fuzzy maximal flow quantity. If the degree of arc membership function of the minimal cut part is not larger than that of arc membership function of the part except the minimal cut, first calcurate nonfuzzy maximal flow quantity, and then can compute the optimal quantity the 3rd step at one time with Max-Min fuzzy operating in the arc capacity of minimal cut and the goal quantity without a great number of recalculation.