• Title/Summary/Keyword: Membership function.

Search Result 757, Processing Time 0.027 seconds

Tuning Method of the Membership Function for FLC using a Gradient Descent Algorithm (Gradient Descent 알고리즘을 이용한 퍼지제어기의 멤버십함수 동조 방법)

  • Choi, Hansoo
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.15 no.12
    • /
    • pp.7277-7282
    • /
    • 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.

Development of an Automatic Expert System for Human Sensibility Evaluation based on Physiological Signal (생리신호를 기반으로 한 자동 감성 평가 전문가 시스템의 개발)

  • Jeong, Sun-Cheol;Lee, Bong-Su;Min, Byeong-Chan
    • Journal of the Ergonomics Society of Korea
    • /
    • v.23 no.1
    • /
    • pp.1-12
    • /
    • 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.

Fuzzy Stretching Method of Color Image (컬러 영상에서의 퍼지 스트레칭 기법)

  • Kim, Kwang-Baek
    • Journal of the Korea Society of Computer and Information
    • /
    • v.18 no.5
    • /
    • pp.19-23
    • /
    • 2013
  • TIn this paper, we propose a novel fuzzy stretching method that adopts a triangle type fuzzy membership function to control the highest and lowest brightness limit dynamically. As an essential procedure to enhance the brightness contrast, stretching is an important procedure in color image processing. While popular Ends-in Search stretching method should be provided fixed minimum and maximum brightness threshold from experience, our proposed method determines them dynamically by fuzzy membership functions. The minimum and maximum limit is determined by computing the lowest and highest pixel value according to the membership degree of our designed triangle type membership function. The experiment shows that the proposed method result in far less skewed histogram than those of Ends-in Search stretching thus successfully verifies its effectiveness.

A Study on the Extension of Fuzzy Programming Solution Method (Fuzzy 계확법의 해법일반화에 관한 연구)

  • 양태용;김현준
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.11 no.1
    • /
    • pp.36-43
    • /
    • 1986
  • In this study, the fuzzy programming is extended to handle various types of membership functions by transformation of the complicated fuzzy programming problems into the equivalent crisp linear programming problems with single objective. It is well-known that the fuzzy programming problem with linear membership functions (i.e., ramp type) can be easily transformed into a linear programming problem by introducing one dummy variable to minimize the worst unwanted deviation. However, until recently not many researches have been done to handle various general types of complicated linear membership functions which might be more realistic than ramp-or triangular-type functions. In order to handle these complicated membership functions, the goal dividing concept, which is based on the fuzzy set operation (i. e., intersection and union operations), has been prepared. The linear model obtained using the goal dividing concept is more efficient and single than the previous models [4, 8]. In addition, this result can be easily applied to any nonlinear membership functions by piecewise approximation since the membership function is continuous and monotone increasing or decreasing.

  • PDF

Anomaly Intrusion Detection using Fuzzy Membership Function and Neural Networks (퍼지 멤버쉽 함수와 신경망을 이용한 이상 침입 탐지)

  • Cha, Byung-Rae
    • The KIPS Transactions:PartC
    • /
    • v.11C no.5
    • /
    • pp.595-604
    • /
    • 2004
  • By the help of expansion of computer network and rapid growth of Internet, the information infrastructure is now able to provide a wide range of services. Especially open architecture - the inherent nature of Internet - has not only got in the way of offering QoS service, managing networks, but also made the users vulnerable to both the threat of backing and the issue of information leak. Thus, people recognized the importance of both taking active, prompt and real-time action against intrusion threat, and at the same time, analyzing the similar patterns of in-trusion already known. There are now many researches underway on Intrusion Detection System(IDS). The paper carries research on the in-trusion detection system which hired supervised learning algorithm and Fuzzy membership function especially with Neuro-Fuzzy model in order to improve its performance. It modifies tansigmoid transfer function of Neural Networks into fuzzy membership function, so that it can reduce the uncertainty of anomaly intrusion detection. Finally, the fuzzy logic suggested here has been applied to a network-based anomaly intrusion detection system, tested against intrusion data offered by DARPA 2000 Intrusion Data Sets, and proven that it overcomes the shortcomings that Anomaly Intrusion Detection usually has.

A construction of fuzzy controller using learning (학습을 이용한 퍼지 제어기의 구성)

  • 안상철;권욱현
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1992.10a
    • /
    • pp.484-489
    • /
    • 1992
  • The inference of fuzzy controller can be considered a mapping from the controller input to membership value. The membership value, a kind of weight, has a role to decide if the input is appropriate to the rule. The membership function is described by several values, which are decided by a learning method. The learning method is adopted from adaptive filtering theory. The simulation shows the proposed fuzzy controller can learn linear and nonlinear functions. the structure of the proposed fuzzy controller becomes a kind of neural network.

  • PDF

A Study on the Determination d Membership Function for Manual Materials Lifting (중량물 수인양에서의 구성함수 결정에 관한 연구)

  • 이종권;송서일
    • Journal of the Korean Society of Safety
    • /
    • v.8 no.4
    • /
    • pp.82-90
    • /
    • 1993
  • Manual lifting, as a part of Manual Materials Handling Activities, is recognized by authorities in the field of occupational health and safety as a major hazard to industrial workers. The most important problem in applying fuzzy model of manual materials lifting is the decision of membership functions on each approaches. : Biomechanical, Physiological, Psychophysical. The primary objectives of this paper suggests to process deciding the most acceptable membership functions for establishing permissible weights on manual lifting activities using fuzzy sets.

  • PDF

퍼지신경망에 의한 퍼지 회귀분석: 품질 평가 문제에의 응용

  • 권기택
    • Proceedings of the Korea Association of Information Systems Conference
    • /
    • 1996.11a
    • /
    • pp.211-216
    • /
    • 1996
  • This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture o fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so 솜 t the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

  • PDF

A Study on the Autonomous Navigation of Mobile Robot using Adaptive Fuzzy Control (적응 퍼지 제어를 이용한 이동 로보트의 자율 주행에 관한 연구)

  • 오준섭;박진배최윤호
    • Proceedings of the IEEK Conference
    • /
    • 1998.10a
    • /
    • pp.433-436
    • /
    • 1998
  • The objective of this paper is to design a adaptive fuzzy controller for autonomous navigation of mobile robot. The adaptive fuzzy controller has an advantage in data processing time and convergence speed. The basic idea of control is to induct membership function and fuzzy inference rules and to scale inducted membership function to suitable robot state. The adaptive fuzzy control method is applied to mobile robot and the simulation results show the effectiveness of our controller.

  • PDF

A Design of Control Chart for Fraction Nonconforming Using Fuzzy Data (퍼지 데이터를 이용한 불량률(p) 관리도의 설계)

  • 김계완;서현수;윤덕균
    • Journal of Korean Society for Quality Management
    • /
    • v.32 no.2
    • /
    • pp.191-200
    • /
    • 2004
  • Using the p chart is not adequate in case that there are lots of data and it is difficult to divide into products conforming or nonconforming because of obscurity of binary classification. So we need to design a new control chart which represents obscure situation efficiently. This study deals with the method to performing arithmetic operation representing fuzzy data into fuzzy set by applying fuzzy set theory and designs a new control chart taking account of a concept of classification on the term set and membership function associated with term set.