• Journal of the Korean Institute of Intelligent Systems
• /
• v.7 no.2
• /
• pp.3-15
• /
• 1997

In order to apply fuzzy logic, two major tasks need to be performed: the derivation of fuzzy rules and the determination of membership functions. These tasks are often difficult and time-consuming. This paper presents an algorithmic method for generating membership functions and fuzzy rules applicable to decision-making problems; the method includes an entropy minimization for clustering analog samples. Membership functions are derived by partitioning the variables into desired number of fuzzy terms, and fuzzy rules are obtained using minimum entropy clustering. In the mle derivation process, rule weights are also calculated. Inference and defuzzification for classification problems are also discussed.

• Proceedings of the KIEE Conference
• /
• 2015.07a
• /
• pp.1343-1344
• /
• 2015

본 연구에서는 증분형 FCM(Incremental Fuzzy C-Means: Incremental FCM) 클러스터링 알고리즘을 기반으로 방사형 기저함수 신경회로망(Radial Basis Function Neural Networks: RBFNN) 패턴 분류기를 설계한다. 방사형 기저함수 신경회로망은 조건부에서 가우시안 함수 또는 FCM을 사용하여 적합도를 구하였지만, 제안된 분류기에서는 빅 데이터간의 적합도를 구하기 위해 증분형 FCM을 사용한다. 또한, 빅 데이터를 학습하기 위해 결론부에서 재귀최소자승법(Recursive Least Square Estimation: RLSE)을 사용하여 다항식 계수를 추정한다. 마지막으로 추론부에서는 증분형 FCM에서 구한 적합도와 재귀최소자승법으로 구한 다항식을 이용하여 최종 출력을 구한다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.86-89
• /
• 2002

본 연구는 객관적인 생리 신호로부터 인간의 감성을 추론할 수 있는 감성 평가 전문가 시스템을 개발하기 위한 첫 번째 단계로, 측정된 생리 신호를 이용하여 인간의 긴장도를 판단하는 알고리즘의 개발이 목표이다. 감성 평가에 관련된 애매함을 수리적으로 취급하기 위해 퍼지 이론을 적용하여 임의의 감성 영역에 속하는 정도를 소속 함수로 정량화 함으로써 감성 평가를 가능하게 하고자 하였다 소속 함수의 결정은 상상을 통해 유발된 긴장/이완의 생리 신호 데이터 베이스 결과를 사용하였다. 그리고 두 가지 이상의 생리 신호 측정 결과와 각 생리 신호의 소속 함수로부터 하나의 최종 결과 (긴장도)를 유추하기 위해서 Dempster-Shafer 증거합 법칙을 적용하였고, 이를 통해 최종적인 긴장도를 도출할 수 있도록 하였다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.1
• /
• pp.13-18
• /
• 2009

Usually, human emotions are vague and change diversely on the basis of the stimulus from the outside. Plutchik classified the fundamental behavioral patterns into eight patterns, named each of them a genuine emotion, and furthermore suggested mixed emotions using a combination of genuine emotions. In this paper, we propose a method for processing Plutchik's emotion model using Multiple Valued Logic(MVL) Automata Model which utilizes the properties of difference in Multiple Valued Logic functions. This proposed emotion processing model can be widely applied to the analysis and processing of emotion data.

• The Korean Journal of Applied Statistics
• /
• v.29 no.2
• /
• pp.291-299
• /
• 2016

This paper discusses how to establish estimable functions when there are fixed and random effects in design models. It proves that estimable functions of mixed models are not related to random effects. A fitting constants method is used to obtain sums of squares due to random effects and Hartley's synthesis is used to calculate coefficients of variance components. To test about the fixed effects the degrees of freedom associated with divisor are determined by means of the Satterthwaite approximation.

• Water for future
• /
• v.29 no.4
• /
• pp.149-160
• /
• 1996

The parameters of the storage function model (SFM) are taken as constants, while they have different values every rainfall events and time of the runoff. Therefore, the results of the SFM show remarkably large errors in general. In this study, the modified sorage function model (MSFM), in which the time variant parameters are introduced, is proposed to improve the SFM which is a conceptual rainfall-runoff model. The fuzzy reasoning is applied as a real-time control method of the time-variant parameters of the proposed model. The applicability of the MSFM was examined in the Bochung river, a tributary of Geum river in Korea. The pattern of predicted outflow hydrograph and peak outflow by the MSFM with fuzzy control are much similar to the measured values in comparison with the results produced by the SFM.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• v.29 no.1
• /
• pp.77-83
• /
• 2005

In collision avoidance problem of a ship, collision risk model is usually set up using the interview results fron experts who sit on a simulator by varying parameters, in which DCPA and TCPA are commonly used. This method, however, has the weakness in that not only it is expensive but also it shows different results depending on the inerviewees and other navigational parameters. In this study, a fuzzy inference system is designed based on own ship's maneuverability verified fron simulation instead of interviewing navigators. The time and distance corresponding to the collision risk value on which avoidance maneuver should be started are set to the minimum marginal time at which own ship starts maneuvering and the minimum marginal distance suggested by marine traffic rules respectively. This system can be recorfigured as a nonlinearity-strengthened one by increasing the number of fuzzy membership functions.

• Journal of Biomedical Engineering Research
• /
• v.18 no.4
• /
• pp.491-498
• /
• 1997

This paper describes the arousal measurement and control system using fuzzy logic to prevent drowsy driving. Sugeno's method was used for fuzzy inference in this study. Arousal evaluation and control criteria were modified from result of Nz-IRI analysis depending on arousal sate. Membership function and rule base of fuzzy inference were determined from the modified arousal level criteria When lRl (Inter-SIR Interval) was shorter than 60sec, outputs of both methods were changed from small to big, but output of three step warning method was same level until the next warning range. Since output of fuzzy inference tracked well the change of subject's arousal level, problems of three step warning method could be overcome by fuzzy inference method Furthermore, the output of the fuzzy inference was highly correlated with Nz(r = 0.99). Therefore, the fuzzy inference method for evaluation and the control of arousal will be more effective at real driving situation than three step warning method.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.11
• /
• pp.27-32
• /
• 2012

In this paper, we propose a fuzzy method that improves the existing problem of the fuzzy filtering algorithm. The proposed fuzzy filtering algorithm separates R, G, and B channels from the color image. Mask information was extracted from separated channels and the brightness of the mean value and median value for channels was applied in the function of the proposed fuzzy method to calculate the membership and achieve application in the inference rule. Also, the membership degrees of R, G, and B were used to distinguish the possibility of noise. The proposed fuzzy method selected three membership functions. If noise is distinguished, the noise is eliminated by selecting the median value or mean value as the relevant pixel value according to the degree of noise. By applying the proposed method in color images, it was verified that the proposed method is more effective in eliminating noise when compared with the conventional fuzzy filtering method.

• Journal of Korean Society of Transportation
• /
• v.29 no.1
• /
• pp.125-134
• /
• 2011

In order to reconstruct vehicle-pedestrian collision accidents, this paper presents a fuzzy tool to estimate accurately the impact velocity of the vehicle using parameters which could be easily collectable at the accident scene. The fuzzy rules and membership functions were set up using number of over 200 domestic and foreign data from accidents and empirical tests and 700 data from multibody simulation experiments. The developed fuzzy tool deduces the category of pedestrian trajectory and impact speed of the vehicle using 4 membership functions and 2 logic rules. The membership function of throw distance was differently set according to the deduced category of trajectories. The implemented fuzzy program was validated through comparing with the domestic and foreign empirical data. The output results agree very well in impact velocities of vehicle resulting the accuracy and usefulness of the developed tool in the reconstruction analysis of vehicle-pedestrian collision accidents.