• Title/Summary/Keyword: 퍼지추론시스템

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The Method of Effective Inference Using Rough Set and Fuzzy Naive Bayes Theory (러프집합과 퍼지 네이브 베이스 이론을 이용한 효율적인 추론 방법)

  • Hwang Jeong-Sik;Son Chang-Sik;Chung Hwan-Mook
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.117-120
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    • 2005
  • 퍼지 규칙 기반 시스템에서 분류 및 경계를 결정하기 위한 방법으로 퍼지 규칙을 학습하는 다양한 방법들이 제안되고 있다. 그리고 추론 규칙간의 상관성을 고려하여 불필요한 속성을 제거함으로써 좀 더 효율적인 추론 결과를 얻을 수 있다. 따라서 본 논문에서는 퍼지 규칙 기반 시스템에서 각 규칙에 따른 결정 테이블를 작성하고 러프집합을 이용하여 불필요한 속성을 제거하였으며 규칙의 확신도에 퍼지 네이브 베이스 이론을 적용한 추론 방법을 제안한다.

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A study of MIMO Fuzzy system with a Learning Ability (학습기능을 갖는 MIMO 퍼지시스템에 관한 연구)

  • Park, Jin-Hyun;Bae, Kang-Yul;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.3
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    • pp.505-513
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    • 2009
  • Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

Development of Fuzzy Inference Engine for Servo Control Using $\alpha$-level Set Decomposition ($\alpha$ -레벨집합 분해에 의한 서보제어용 퍼지 추론 연산회로의 개발)

  • 홍순일;이요섭
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.3
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    • pp.50-56
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    • 2001
  • As the fuzzy control is applied to servo system, the hardware implementation of the fuzzy information systems requires the high speed operations, short real time control and the small size systems. The aims of this study is to develop hardware of the fuzzy information systems to be apply to servo system. In this paper, we propose a calculation method of approximate reasoning for fuzzy control based on $\alpha$ -level set decomposition of fuzzy sets by quantize $\alpha$ -cuts. This method can be easily implemented with analog hardware. The influence of quantization Bevels of $\alpha$-cuts on output from fuzzy inference engine is investigated. It is concluded that 4 quantization levels give sufficient result for fuzzy control performance of dc servo system. The hardware implementation of proposed operation method and of the defuzzification by gravity center method which is directly converted to PWM actuating signal is also presented. It is verified useful with experiment for dc servo system.

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Cursor Control by the Finger Movement Using Fuzzy Inference (퍼지 추론을 적용한 손가락 이동에 의한 커서 제어)

  • 신일식;손영선
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.05a
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    • pp.195-198
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    • 2002
  • 본 논문에서는 영상 해석 알고리즘의 하나인 원형 패턴 벡터 알고리즘과 퍼지 추론을 사용하여 손가락으로 커서를 제어하는 인터페이스를 구현하였다. 최대 원형 이동법을 이용하여 물체의 무게 중심점을 찾아서 그 점에서 원형 패턴 알고리즘을 적용하면 외곽가지 거리 스펙트럼을 추출할 수 있다. 손에 대한 조건을 제시하여 일치하는 스펙트럼이 추출되면 손으로 인식하게 하였다. 커서의 방향제어는 크게 수평 방향과 수직 방향으로 나눌 수 있다. 커서의 수평 방향은 거리 스펙트럼에 의해 지시 손가락 부분을 찾아서 평면 좌표로 해석하여 제어 하였고, 커서의 수직 방향은 최대 원형의 크기와 손의 최대 크기를 입력 받아 퍼지 추론하여 커서의 위치를 제어 하였다. 퍼지 추론을 이용함으로써 기존의 불연속적인 커서의 수직 방향 제어를 좀 더 유연하고 연속적으로 제어 할 수 있었다.

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Design of Fuzzy Inference-based Deterioration Diagnosis System through Different Image (차 영상을 통한 퍼지 추론 기반 열화 진단 시스템 설계)

  • Kim, Jong-Bum;Choi, Woo-Yong;Oh, Sung-Kwun;Kim, Young-Il
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.1
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    • pp.57-62
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    • 2015
  • In this paper, we design fuzzy inference-based deterioration diagnosis system through different image for rapid as well as efficient diagnosis of electrical equipments. When the deterioration diagnosis of the electrical equipment starts, abnormal state of assigned area is detected by comparing with the temperature of the first normal state of the area. Deterioration state of detected area is diagnosed by using fuzzy inference algorithm. In the fuzzy inference algorithm, fuzzy rules are defined by If-then form and are described as look-up table. Both temperature and its ensuing variation are used as input variables. While triangular membership function is used for the fuzzy input variables of fuzzy rules, singleton membership function is used for the output variable of fuzzy rules. The final output is calculated by using the center of gravity of fuzzy inference method. Experimental data acquired from individual electrical equipments is used in order to evaluate the output performance of the proposed system.

A Study on Optimal fuzzy Systems by Means of Hybrid Identification Algorithm (하이브리드 동정 알고리즘에 의한 최적 퍼지 시스템에 관한 연구)

  • 오성권
    • Journal of the Korean Institute of Intelligent Systems
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    • v.9 no.5
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    • pp.555-565
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    • 1999
  • The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

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A Music Recommendation System Suitable to the Individual Taste (개인 취향에 맞는 음악 선곡 시스템)

  • 조용성;강은영;손영선
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.435-438
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    • 2002
  • 본 논문은 웹 상에서 음악을 듣는 사용자의 음악 취향을 평가 한 후, 취향에 맞는 인터페이스를 추천하는 시스템을 구현하였다. 초기 음악 취향 평가 단계에서는 평가 요소인 장르, 가수, 최신곡에 대한 사용자 데이터와 평가 요소에 대한 실험을 통해 얻은 중요도를 이용하여 퍼지측도.적분을 수행한다. 수행 결과 값이 높은 음악의 평가 요소에 의해 인터페이스를 추천하고, 추천된 인터페이스에 대한 선택 곡 수와 들은 시간으로 퍼지 추론을 통해 인터페이스에 대한 만족도를 평가한다. 평가된 만족도에 의해 중요도를 변경시킴으로써 사용자의 취향에 맞는 인터페이스를 제공하는 시스템 을 제안한다.

MIMO Fuzzy Reasoning Method using Learning Ability (학습기능을 사용한 MIMO 퍼지추론 방식)

  • Park, Jin-Hyun;Lee, Tae-Hwan;Choi, Young-Kiu
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.175-178
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    • 2008
  • Z. Cao had proposed NFRM(new fuzzy reasoning method) which infers in detail using relation matrix. In spite of the small inference rules, it shows good performance than mamdani's fuzzy inference method. But the most of fuzzy systems are difficult to make fuzzy inference rules in the case of MIMO system. The past days, We had proposed the MIMO fuzzy inference which had extended a Z. Cao's fuzzy inference to handle MIMO system. But many times and effort needed to determine the relation matrix elements of MIMO fuzzy inference by heuristic and trial and error method in order to improve inference performances. In this paper, we propose a MIMO fuzzy inference method with the learning ability witch is used a gradient descent method in order to improve the performances. Through the computer simulation studies for the inverse kinematics problem of 2-axis robot, we show that proposed inference method using a gradient descent method has good performances.

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An Aptitude Test System using Fuzzy Reasoning (퍼지 추론을 적용한 적성 평가 시스템)

  • 안수영;김두완;정환묵
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2002.12a
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    • pp.451-454
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    • 2002
  • 본 논문에서는 개인의 적성을 판단하는 문제를 처리하기 위한 가중치 퍼지추론 알고리즘을 제시하고, 지식표현을 위해 퍼지 집합 이론과 퍼지 생성 규칙들을 이용하였다. 거리척도에 서는 퍼지값이 높은 구간의 척도를 낮은 구간의 척도에 비례하여 유사성을 구하였다. 또한, 가중치를 정량화한 값과 척도값을 연산하여 유사성을 나타냈고, 추출된 항목과 규칙과의 가능성을 구하였다. 여기서, 결과는 수검자들이 응답한 값들에 따라 임의의 직업군이 적당한 지를 나타내기 위해 확신도로 해석하였다.

Design of Simple-structured Fuzzy Logic System based Driving Controller for Mobile Robot (단순구조 퍼지논리시스템을 이용한 이동 로봇의 주행 제어기 설계)

  • Choi, Byung-Jae;Jin, Sheng
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.1
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    • pp.1-6
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    • 2012
  • In this paper, we present an obstacle avoidance control algorithm for mobile robots based on SFLC (single-input fuzzy logic controller) with an efficient fuzzy logic look-up table to replace the traditional complicated operation. This method achieves better performance than traditional methods in terms of efficiency. The output of a SFLC leads the robot to the target automatically although many obstacles on the path. Our experiments show that the robot has good performance in the view of path tracking and other efficiency.