A Fuzzy Classifier which deals with very confusing objects is proposed. Naturally this classifier heavily relies on the nulti-feature decision-making procedure. For a simple example, this classifier is applied to the recognition of confusing handwritten numerals 4,6 and 9 The characteristic variables used in this paper are the existence of a loop and the relative location of the starting or ending points(SEP). Thus each sample of handwritten numerals 4, 6 and 9 is classified in one of the 6 groups which are divided according to the sample structure. Each group has its own classifying rules. Also the method of rule-generation using genetic algorithms in each group is proposed.

This paper describes a system that can be used to recognize an unknown material regardless of the fuzzy neural network(FNN). There are some problems to realize the recognition system using temperature response. It requires too many memories to store the vast temperature response data and it has to be filtered to remove noise which occurs in experiment. And the temperature response is influenced by the change of ambient temperature. So, this paper proposes a practical method using curve fitting to remove above problems of memories and noise. and FNN is proposed to overcome the problem caused by the change of ambient temperature. Using the FNN which is learned by temperature responses on fixed ambient. Temperatures and known thermal conductivity, the thermal conductivity of the material can be inferred on various ambient temperatures. So the material can be recognized by the thermal conductivity.

A Practical application of self-tuning fuzzy controller to a multi-input multi-output complex system of a vehicle engine is investigated. The ovjective is to design a controller to improve the transient performance in torque and RPM mode changes. For the performance improvement in the multivariable comples system, the self-tuning function of internal parameters is essential and practical. The measured output variables using different control schemes are compared the advanteges of the self-tuning fuzzy logic controller are better output performances and the effectiveness in the controller design using many parameters.

One dimensional optimization problem is considered, we propose a method to find the global minimum of one-dimensional function with on gradient information but only the finite number of input-output samples. We construct a learning network which has a good learning capability and of which global maximum(or minimum) can be calculated with simple calculation. By teaching this network to approximate the given function with minimal samples, we can get the global minimum of the function. We verify this method using some typical esamples.

In this paper, we propose a retrieval system using knowledges of database expressed linguistically, where the relation between data are constructed by FCM. Several algorithms have been proposed to solve the major problem in the conventional retrieval system that the system doesn't reply in case of no data equal to user's query, and to express knowledge of database linguistically. This paper proposes the improved method of adding new cluster and the method of retrieving database from user's query. The validity of this retrieval system is shown by applying its algorithm to an example : the mail order service in post office.

A novel definition for fuzzy mathematical morphology is described The generalized-mean operator plays the key role for this definition. Several hard constraints for standard generalized-mean have been eliminated. Complete mathematical description for obtaining fuzzy erosion and dilation is provided. The definitions are well suited for neural network implementation. Therefore, the parameters for the fuzzy definition can be optimized using neural network learning paradigm.

A shared-weight neural network that performed classification based on the features extracted with the fuzzy morphological operation is introduced. Learning rules for the structuring elements, degree of membership, and weighting factors are also precisely described. In application to handwritten digit recognition problem, the fuzzy morphological shared-weight neural network produced the results which are comparable to the state-of-art for this problem.

Output performance improvement using fuzzy logic to the conventional control scheme for a magnetic levitation system is presented in this paper, Adverse characteristics of nonlinearity, unstability, system parameter variation, etc, in the levitation system are partially overcome by the general fuzzy control action. Using a PD type compensator, a coarse framework of output performance is provided to the levitation system. Then a fine regulation to the output performance requirement is obtained by the natural description of the control action in the form of fuzzy logic controller. This control action soothes the adverse characteristics of the levitation system. In this way a better output performance can be obtained in a real time experiment.

In this paper are proposed robust iterative learning control(ILC) algorithms for both linear continuous time-invariant system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithm.

In this paper we introduce the notions of a TL-finite state machine, TL-retrievability, TL-separability, TL-connectivity and discuss their basic properties.

This paper presents a system which recognizes the Korean Sign Language(KSL) and translates into normal Korean speech. A sign language is a method of communication for the deaf-mute who uses gestures, especially both hands and fingers. Since the human hands and fingers are not the same in physical dimension, the same form of a gesture produced by two signers with their hands may not produce the same numerical values when obtained through electronic sensors. In this paper, we propose a dynamic gesture recognition method based on feature analysis for efficient classification of hand motions, and on a fuzzy min-max neural network for on-line pattern recognition.

In medical diagnostic process we are dealing with the preliminary diagnosis based on the interview chart. We will quantify the qualitative information of a patient by dual scaling and establish both prototypes of fuzzy diagnostic sets and the fuzzy linear regressions. Its utility is shown in the diagnosis of headache and CAFDDH.

In this paper, a method is presented for finding an optimal temperature control pattern in microwaveoven using genetic algorithm. Power spectrum of temperature variance of charcoal is obtained and oven system modeling with fuzzy-neural-network is explained. Fan on/off timing is converted to strings in gene pool and then genetic iterations make the power spectrum of simmulated temperature variance of microwave oven closer to that o charcoal.

In this paper, the fuzzy controls for the structures subjected to seismic forces are studied The structural models of two and three degrees of freedom are considered in numerical examples. The related simulation results show that the technique of Fuzzy control is useful for reducing the relative displacement.

본 연구는 퍼지모델링을 이용한 고속 소형선의 전체 저항곡선 및 마력곡선을 고속 소형선의 선형요소 자료들로부터 퍼지모델링 알고리즘을 통해 도출하고, 그 결과를 모형시 험 결과와 비교하고 있다. 또한 퍼지모델링 알고리즘에 의한 전체 저항곡선 및 마력곡선이 고속 소형선의 선형요소 결정에 효율적으로 적용됨을 보이고 있다.

본 연구에서는 유전자 알고리즘과 Hooke & jeeves 방법을 적용한 퍼지모델링 기법 을 이용하여 저속비대선에서 선미형상의 주요치수를 결정하고, 이를 실적선과 비교하였다.

Recently, the vehicle engine requried precision control of Air-Fuel rate and rigid restriction of exhaust gas. Therefore, we demanded excellent measuring equipment so as to improve of engine performance. Specially, throttle valve control is very important part in the engine control, because structure of engine dynamometer system is very important part in the engine control, because structure of engine dynamometer system is very complicate and it has nonlinear elements which is influenced of disturbance about vibration, a heat, a cooling, energy loss so on. In this study, we propose the method that the control technique using Fuzzy Look-up table and we obtained the satisfying result from realized the control system.

A new technique using integer programming based on fuzzy multi-criteria function is proposed for generator maintenance scheduling. Minimization maintenance delay cost and maximization reserve power are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria integer programming is used. In the maintenance scheduling, a characteristic feature of the presented approach is that the crisp constraints with uncertainty can be taken into account by using fuzzy set theory and so more flexible solution can be obtained. The effectiveness of the proposed approach is demonstrated by the simulation results.

LIBL(Linguistic Instruction Based Leaning) is an effective learning algorithm for fuzzy controller which interpretes and uses natural language of human The possibiliy of the LIBL algorithm to the fuzzy control of dynamic systems is investigated in this paper. Rise time, percent overshoot, and steady stste are proposed as suitable meaning elements for dynamic systems. A supervisor is able to give "higer-level linguistic instruction" to the learning algorithm through these three meaning elements Simulation results for a DC servo motor show the validity of the proposed algorithm.

This paper presents a novel SOFLIC(self organizing fuzzy logic intelligent controller) for reactor rod control system in nuclear power plant. The output of fuzzy controller is gener ated by using two signal : the error between reference and average temperature, and the error between reference and neutron flux-converted temperatures. Flexibility of the controller is enhanced by using self-organizing feature and the controller respond to variation of system parameter with more precision. performances of the SOFLIC and PID are simulated with the model developed for a nuclear power plant. The SOFLIC is superior to PID : SOFLIC provides more rapid load following capability. more robustiness for variation in process dynamics and minimization of engineer's mistakes in controller design.

In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed fuzzy GMDH modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) algorithm and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH algorithm and fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnaceare those for sewage treatment process are used for the purpose of evaluating the performance of the proposed fuzzy GMDH modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

Driving maneuver in car following are affected by not only the factors related to road structure and traffic condition, but also the factors related to driver's cognition to them. So the aim of this research this to model the relation of driver's cognition for car-following distance considering driver's fuzziness for imformation cognition, As a result, driver's cognition of car-following distance model with fuzzy number is proposed. The 'width', which characterizes the fuzzy number can introduce car-following informtion into the model.

In order to eliminate position errors existing at the steady state in the motion control of robotic maniprlators, a new fuzzy control algorithm is proposed using three variables, position error, velocity error and integral of position errors as input variables of the fuzzy controller, This controller is applied to the tracking control of robotic manipulators in Cartesian space. Three dimensional look-up table is used to reduce the computational time in rel-time control. Simulation and experimental studies are conducted to evaluate the control performance for the two axis direct drive SCARA robot system.

본 논문데서는 부하외란이나 시스템 내부 파라미터의 변동시에 적응력이 저하되는 종래의 PI제어기와, 정상상태 잔류편차가 존재하는 퍼지 제어기의 단점을 극복하기 위한 적 응 퍼지 제어 기법을 제안하였고, 이를 도립 진자 시스템에 적용하였다. 운송차의 위치 및 진자 각도의 오차, 오차의 변화량에 따라 퍼지 추론을 행하여 PI 제어기의 가중치를 결정하 는 구조로, P제어기는 운송차 및 진자의 오차가 과도 상태에서의 영역에서 사용되어 속응성 과 고정도의 특성을 얻는다. 1제어기는 정상상태에서의 정도 향상에 이용되었다. 특히, 제안 하는 적응 퍼지 제어기는 운송차의 위치 오차에 대한 PI 동작과, 진자의 각도 오차에 대한 PI 동작을 각각 퍼지 추론에 의해 부드럽게 전환함으로서 고유 불안정의 시스템인 도립 진 자 시스템의 안정화 제어에 적용하였다.

In this paper, we designed the speed controller with high accuracy and speedy steady-state response, in Induction motor control system, Fuzzy P-1 controller of Induction motor using Microprocessor have an appropriate fuzzy rule matrix (which is 2-separate Look-up Table) The usefulness of proposed fuzzy P-1 controller will be confirmed by experiments which we compare with conventional P-1 controller.

본 연구에서는 퍼지 클러스터링 알고리즘과 변수선택 방법을 이용하여 모델의 구조 동정을 행하고, 신경회로망의 Back-propagation 학습방법을 이용하여 파라메터동정을 행하 는 새로운 퍼지모델링 알고리즘을 제안하였다. 실제 데이터를 이용하여 전력부하예측시스템 을 설계하였으며 그 결과 타당성을 입증하였다.

This paper presents the calculating method of optimum correction mass within permissible vibration limits for rotating machinery in two-plane field balancing. Basic technique of this method based on influence coefficient method, is graphic vector composition that the resultant of two influence vectors obtained by trial mass have to be equilibrium with initial vibration vector in the each correction plane. Genetic algorithm which is a search algorithm based on the mechanics of natural selection and natural genetics is used for vector composition, and SUMT method is used to objective function which seeks optimum correction mass for balancing a rotor.

본 논문에서는 주어진 입출력 데이터로부터 유전자 알고리즘을 이용하여 퍼지제어 기를 자동 생성하는 방법에 대하여 기술한다. 주어진 입출력 데이터를 표현하는 퍼지제어기 는 각 유전자에 암호화되고, 퍼지제어기를 표현하는 각 유전자들은 서로 정보를 교환함으로 써 주어진 데이터를 적절히 표현하는 퍼지제어기를 탐색하게 된다. 유전자는 각 입력 변수 의 언어항을 정의하고, 퍼지제어규칙은 정의된 언어항과 주어진 데이터로부터 생성된다. 탐 색과정에서 퍼지제어기의 제어규칙과 각 입력변수의 언어항의 개수와 위치는 계속 변화하여 주어진 입출력 데이터를 잘 설명하는 퍼지제어기를 찾는다.

Conventional linear control fails to provide precise positioning of a control object under the influence of friction, deadzone, saturation, etc. This paper proposes a high-precision control scheme for a precise point-to-point positioning system, called an X-Y table, even under the same influences above. The proposed scheme is composed of a fuzzy precompensator and a PD controller. The fuzzy precompensator is employed to improve the performance of the PD controller. Its fuzzy rules are obtained from experimental evolutionary programming (EP), not from an expert. The effectiveness of the scheme is demonstrated by experiments on the X-Y table. with a positioning error of within 1$\mu\textrm{m}$.

A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature or feature subset among all the available features is selected based on fitness function in genetic algorithm which is inversely proportional to classification error, balance between cluster, number of feature used. The proposed design scheme is applied to the handwtitten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

In this paper, we introduce the identification model of dynamic system using the neural networks, We propose two identification models. The output of the parallel identification model is a linear combination of its past values as well as those of the input. The series-parallel model is a linear combination of the past values in the input and output of the plant. To generate stable adaptive laws, we prove that the series-parallel model is found to be proferable.

본 논문에서는 신경회로망의 학습능력을 이용하여 AC 모터의 속도제어에 이용된 기 존의 PI제어기의 문제점을 보완하고자 한다. 기존의 아날로그 PI제어기에서는 각 비례, 적분 파라메타를 개발자가 조정하여 고정하면 부하가 변동될 경우 적응성이 떨어지는 문제점을 안고 있었다. 본 논문에서 제시된 디지털 신경망제어기는 학습을 통해 새로운 환경에 적응 가능하다는 점에 가정하여 설계하고 성능을 비교 평가하였다. 본 논문에서 사용된 신경회로 망의 구조는 신경망중에서 가장 범용적으로 사용되는 다층 퍼셉트론 모델구조를 선택하였 다. 신경망 제어기장치로는 인텔 8097 마이크로 콘트롤러를 이용하였다.

In this paper, we demeonstrate that neural networks can be used effectively for the control of nonlinear dynamical system. To adaptively control a plant, there are two distinct approach. these are direct control and indirect control. Both direct and Indirect adaptive control are trained using static back propagation. In indirect, using the resulting identification model, which contains neural networks and linear dynamical elements as subsystems, the parameters of the controller are adjusted.

본 논문은 일반화된 다중 수상돌기 적 (GMDP : Generalized Multi Dendrite Product) 유닛트 신경망을 이용한 PID 적응 위치제어기를 구성하여 직류 서어보 전동기의 위치제어를 실시간 처리 하였다. 제안한 제어기를 위치제어에 적용시켜 실험한 결과 기존의 MLP 신경망 제어기를 이용한 것 보다도 샘플시간을 줄일 수 있다는 장점으로 정밀한 제어 가 가능하다는 것을 확인할 수 있었다. 학습규칙은 기존의 역전파 학습방법이 GMDP 신경 회로망에 적용되었다.

This paper presents an efficient design method to realize an associative memory with BSB neural networks by means of the parametrization of the solution space and searching for the optimal solution using an evolution program. In particular, the performance index based on DOA analysis in this paper may make and associative memory implementation to reach on the level of practical success.

In this paper, we propose "a graph structured fuzzy system" which is able to represent the fuzzy system with a graph and optimizes the fuzzy membership functions and fuzzy rule bases using genetic algorithms. It performs the structure identification phase and parameter tuning phase simultancously through the evolutionary process. Additionally, it alleviates some of the drawbacks associated with the current fuzzy construction method with respect to the explosive increase of fuzzy rules which is inevitably encountered whenever the fuzzy systems are applied to problems with the high-dimensional input space.

In CAI, it is very important to evaluate the grade of understanding which students reach about the scope of problem which students are studying. In this paper, to find out students' learning achievement, we make students reply to test which the system presents and then lead evaluation result using fuzzy number about answer result. Besides, we define the degree of prior knowledge of studentsd as conditioned fuzzy number and use existing fuzzy accuracy production function begore the stage of using fuzzy number, Next, we apply conditioned fuzzy number to accuracy degree of answer produces by this function. Through this, we come to the conclusion that evaluation result as to the same answer result is changed according to the degree of prior knowledge about the scope which students are studying.

최근 규칙베이스 추론과 사례베이스 추론의 통합화에 의한 추론이 다양하게 시도되 고 있다. 본 논문에서는 규칙과 사례를 동일한 형태로 표현하고, 규칙베이스와 사례베이스를 통합한 새로운 통합 추론 방법을 제안한다. 지식은 논리의 기하학적 모델을 이용하여 정보 를 논리적으로 해석하며, 동일한 형태로 표현된 규칙과 사례를 Boole 함수의 미분 및 전개 방법을 이용하여 추론하는 방법을 제안하고 응용예를 통하여 확인하다.

본 논문은 컴퓨터 시각을 이용하여 동적 제스쳐를 인식하기 위한 효율적인 지식 표 현 기법의 개발을 목표로 한다. 제스쳐란 시각적인 언어로서 소리를 대신하여 몸짓이나 손 짓을 통하여 자신의 생각이나 의도를 전달하는 보조적인 의사 전달 수단이다. 제안된 기법 은 여러 다양한 지식을 통합하여 총체적으로 표현하기에 적합한 프레임 구조를 기반으로 한 다. 프레임 지식을 물체의 특성을 표현하는 객체 지식, 물체의 움직임을 표현하는 행동 지 식, 그리고 객체 지식과 행동 지식의 순서화 된 집함으로써 동적인 제스쳐를 표현하는 스키 마로 분류한다.

In this study we present the inverse correlation method to select the exploratory variables, while Sugeno used RC method in his paper[6] We assume linear model with measurement error variables as in Fuller's Book[9]. we provide possibilistic linear model and predict the fuzzy response variable in case of fuzzy exploratory variables. By plotting data we can divide them for piecewise plane and provide the piecwise possibilistic linear model. If the exploratory variable is fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal variable or interval variable, then we estimate fuzzy trapezoidal response variable respondent to it. We will illustrate using Nonlinear System data in Sugeno's paper

Using the representation theorem of fuzzy number, we give the Radon-Nikodym theorem for fuzzy-number-valued measures

This paper discuss some properties of non-monotonic fuzzy measures of Ф -bounded variation. We show that there is an example of Ф such that $\beta$V(x, F) is a proper subspace of Ф$\beta$V(x, F) And also, we prove that Ф$\beta$V(x, F) is a real Banach space. Furthermore, we investigate some properties of non-monotonic fuzzy Ф -measures.

We define a PL-limit structure and a PL-Cauchy structure and obtain a completion of a separated PL-Cauchy structure.

We redefine the sup-min product of fuzzy subsets and discuss the redefined sup-min products of fuzzy subgroupoids, fuzzy submonoids and fuzzy subgroups. And we study lattice structures of the lattices of fuzzy subgroupoids, fuzzy submonoids and fuzzy subgroups.

The notion of Ap* of a fuzzy subgroup A is introduced. Using the notion, we characterize fuzzy subgroups and show that every commutative fuzzy subgroup characterized as the intersection of its all minimal fuzzy p*-subgroups.

In this paper we tried to apply the concepts of fuzzy set to Lie algebra, to define some concepts related to fuzzy set to discuss their properties and relations among them.

We define a fuzzy regular modification and fuzzy regular series. And we investigate some properties of fuzzy regular modification with respect to fuzzy initial convergence structure

In this note, we give generalized common fixed point theorems for sequences of fuzzy mappings on Menger probabilistic metric spaces.

In this paper, we introduce fuzzy completely pre-irresolute and fuzzy weakly completely preirresolute mappings between fuzzy topological spaces, and study these mappings in relation to some other types of already known mappings.

We shall define the usual fuzzy distance between two fuzzy points in R, the set of all real, numbers, using the usual distance between two points in R. Applying the notion of this usual fuzzy distance, we construct the usual fuzzy topology for R, introduce the notions of lower, stationary and upper cover and obtain the fuzzy Heine-Borel theorem.

We study likely mean value theorem with respect to integral of real mapping between fuzzy bound. This is the main purpose of this paper, which investigates ideas in Dubois & Prade [2,3,4]

We introduce the concepts of generalized closed fuzzy set(breifly g-closed fuzzy set) and generalized fuzzy continuity (briefly g-fuzzy continuity), and investigate their some properties. When A is a fuzzy set in a fuzzy topological space, we denote the closure of A, the interior of A and the complement of A as CA(a) and CA, respectively

We introduce new weak forms of fuzzy continuity and fuzzy closed mapping(which we call a-fuzzy continuity and a-fuzzy closed mapping). And we investigate some of the basic properties of a-fuzzy continuous mapping and a-fuzzy closed mappings.

Kandil[5] introduced and studied the notion of fuzzy bitopological spaces as a natural generalization of fuzzy topological In [10], Sampath Kumar introduced and studied the concepts of ( i, j)-fuzzy semiopen sets, fuzzy pairwise semicontinuous mappings in the fuzzy bitopological spaces. Also, he defined the concepts of ( i, j)-fuzzy -open sets, ( i, j)-fuzzy preopen sets, fuzzy pairwise -continuous mappings and fuzzy pairwise precontinuous mappings in the fuzzy bitopological spaces and studied some of their basic properties. In this paper, we generalize the concepts of fuzzy -open sets, fuzzy -continous mappings ？ 새 Mashhour, Ghanim and Fata Alla[6] into fuzzy bitopological spaces, We first define the concepts of ( i, j)-fuzzy -open sets and then consider the generalizations of fuzzy pairwise -continuous mappings is obtained Besides many basic results, results related to products and graph of mapping are obtained in the fuzzy bitopological spaces.

We study fuzzy symmetric subgroups and obtain some properties of fuzzy symmetric subgroups of symmetric groups.

전기 유압식 좌심실 보조장치에서 모터 전류 파형을 정보로 하여 작동기의 이완기 속도를 조절함으로써 좌심방으로부터 유입되는 혈류량을 조절하는 알고리즘을 개발하였다. 좌심실 보조장치(Left Ventricular Assist Device, LVAD)는 허혈성 심장질환 등으로 좌심실 의 혈액 박출 기능이 저하된 환자에게 시술하여 정상 상태의 심박출량을 유지할 수 있도록 하는 보조 혈액 박출 기능이이다. 전기 유압식 좌심실 보조장치에서는 혈액의 유입이 능동 적으로 이루어지므로, 좌심방 함몰로 인한 심근 손상 및 외부 공기 유입으로 인한 색전증을 방지하기 위해 유입혈류량을 현재 좌심방내의 상태에 따라 적절히 조절해 주어야 한다. 좌 심방 내의 혈액량 정도는 혈액을 유입해 내는 작동기의 이완기 동작 시에 소모되는 에너지 크기에 반영되고, 작동기를 구동하는 모터에 들어가는 전류의 크기는 작동기에 공급되는 에 너지에 비례하므로, 이전류 파형의 정보들을 통해 좌심방내의 상태를 추정해 볼 수 있다. 본 논문에서는 퍼지로직을 적용하여 모터 전류 파형의 정보들을 통해 좌심방 내의 상태를 추정 해 볼 수 있다. 본 논문에서는 퍼지로직을 적용하여 모터 전류 파형의 이상 유무를 판단한 뒤 에에 따라 작동기의 이완기 속도를 조절하는 알고리즘을 개발하여 모의순환장치 실험을 통해 그 실효성을 검증한 결과를 정리하였다.