• 제목/요약/키워드: Fuzzy Functions

검색결과 944건 처리시간 0.028초

Temporal Search Algorithm for Multiple-Pedestrian Tracking

  • Yu, Hye-Yeon;Kim, Young-Nam;Kim, Moon-Hyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권5호
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    • pp.2310-2325
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    • 2016
  • In this paper, we provide a trajectory-generation algorithm that can identify pedestrians in real time. Typically, the contours for the extraction of pedestrians from the foreground of images are not clear due to factors including brightness and shade; furthermore, pedestrians move in different directions and interact with each other. These issues mean that the identification of pedestrians and the generation of trajectories are somewhat difficult. We propose a new method for trajectory generation regarding multiple pedestrians. The first stage of the method distinguishes between those pedestrian-blob situations that need to be merged and those that require splitting, followed by the use of trained decision trees to separate the pedestrians. The second stage generates the trajectories of each pedestrian by using the point-correspondence method; however, we introduce a new point-correspondence algorithm for which the A* search method has been modified. By using fuzzy membership functions, a heuristic evaluation of the correspondence between the blobs was also conducted. The proposed method was implemented and tested with the PETS 2009 dataset to show an effective multiple-pedestrian-tracking capability in a pedestrian-interaction environment.

서비스 블루프린트와 FTA를 이용한 서비스 신뢰도 평가모델 (Evaluation Model of Service Reliability Using a Service Blueprint and FTA)

  • 유정상;오형술
    • 산업경영시스템학회지
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    • 제35권4호
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    • pp.194-201
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    • 2012
  • Because the difference between products and services are getting less and less, service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs under today's competitive market environment. The value of services depends on service reliability that is identified by satisfaction derived from the relationship between customer needs and service providers. In this paper, we extend concepts from the fault tree analysis for reliability analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using service blueprint and FTA. We can identify the failure mode of service in a service delivery process with a service blueprint. The fuzzy membership function is used to characterize the probability of failure based on linguistic terms. FTA is employed to estimate the reliability of service delivery processes with risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

Multi-Frame Face Classification with Decision-Level Fusion based on Photon-Counting Linear Discriminant Analysis

  • Yeom, Seokwon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제14권4호
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    • pp.332-339
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    • 2014
  • Face classification has wide applications in security and surveillance. However, this technique presents various challenges caused by pose, illumination, and expression changes. Face recognition with long-distance images involves additional challenges, owing to focusing problems and motion blurring. Multiple frames under varying spatial or temporal settings can acquire additional information, which can be used to achieve improved classification performance. This study investigates the effectiveness of multi-frame decision-level fusion with photon-counting linear discriminant analysis. Multiple frames generate multiple scores for each class. The fusion process comprises three stages: score normalization, score validation, and score combination. Candidate scores are selected during the score validation process, after the scores are normalized. The score validation process removes bad scores that can degrade the final output. The selected candidate scores are combined using one of the following fusion rules: maximum, averaging, and majority voting. Degraded facial images are employed to demonstrate the robustness of multi-frame decision-level fusion in harsh environments. Out-of-focus and motion blurring point-spread functions are applied to the test images, to simulate long-distance acquisition. Experimental results with three facial data sets indicate the efficiency of the proposed decision-level fusion scheme.

적응성 있는 차분 진화에 의한 함수최적화와 이벤트 클러스터링 (Function Optimization and Event Clustering by Adaptive Differential Evolution)

  • 황희수
    • 한국지능시스템학회논문지
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    • 제12권5호
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    • pp.451-461
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    • 2002
  • 차분 진화는 다양한 형태의 목적함수를 최적화하는데 매우 효율적인 방법임이 입증되었다 차분 진화의 가장 큰 이점은 개념적 단순성과 사용의 용이성이다. 그러나 차분 진화의 수렴성이 제어 파라미터에 매우 민감한 단점이 있다. 본 논문은 새로운 교배용 벡터 생성법과 제어 파라미터의 적응 메커니즘을 결합한 적응성 있는 차분 진화를 제안한다. 이는 수렴성을 해치지 않으면서 차분 진화를 보다 강인하게 만들며 사용이 쉽도록 해준다. 12가지 최적화 문제에 대해 제안한 방법을 시험하였다. 적응성 있는 차분 진화의 응용 사례로써 이벤트 예측을 위한 교사 클러스터링 방법을 제안한다. 이 방법을 진화에 의한 이벤트 클러스터링이라 부르며 데이터 모델링 검증에 널리 사용되는 4 가지 사례에 대해 그 성능을 시험하였다.

전력시스템 고조파 상태 춘정에서 GA를 미용한 최적 측정위치 선정 (Optimal Placement of Measurement Using GAs in Harmonic State Estimation of Power System)

  • 정형환;왕용필;박희철;안병철
    • 대한전기학회논문지:전력기술부문A
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    • 제52권8호
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    • pp.471-480
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    • 2003
  • The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

비드 높이 및 조인트 추적의 실시간 제어 연구 (A Study on Real-time Control of Bead Height and Joint Tracking)

  • 이정익;고병갑
    • 한국공작기계학회논문집
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    • 제16권6호
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    • pp.71-78
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    • 2007
  • There have been continuous efforts to automate welding processes. This automation process could be said to fall into two categories, weld seam tracking and weld quality evaluation. Recently, the attempts to achieve these two functions simultaneously are on the increase. For the study presented in this paper, a vision sensor is made, and using this, the 3 dimensional geometry of the bead is measured in real time. For the application in welding, which is the characteristic of nonlinear process, a fuzzy controller is designed. And with this, an adaptive control system is proposed which acquires the bead height and the coordinates of the point on the bead along the horizontal fillet joint, performs seam tracking with those data, and also at the same time, controls the bead geometry to a uniform shape. A communication system, which enables the communication with the industrial robot, is designed to control the bead geometry and to track the weld seam. Experiments are made with varied offset angles from the pre-taught weld path, and they showed the adaptive system works favorable results.

선박의 개념 설계 지원용 뉴로 퍼지 시스템 개발 (A Development of Neurofuzzy System for a Conceptual Design of Ship)

  • 김수영;김현철
    • 대한조선학회논문집
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    • 제35권3호
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    • pp.79-87
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    • 1998
  • 본 연구는 선박의 개념 설계 단계에서 설계 변수-주요 치수 및 선형 요소 등-들을 효율적으로 도출할 수 있는 선박 설계용 뉴로 퍼지 시스템 개발을 내용으로 한다. 선박 설계용 뉴로 퍼지 시스템(NeFHull)은 주어진 입출력 데이터에 대한 정보를 퍼지 이론으로 처리하여, 이를 신경회로망에 적용하는 것으로, 무차원화한 입출력 데이터로부터 소속 함수로 입력 패턴을 재 정의한 후, 신경 회로망으로 그 정보를 처리한다. 신경 회로망 학습에는 혼합 학습 방법을 사용하였으며, 수학적 공학적 예를 통해 본 방법을 유용성을 검토하였다.

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A system model for reliability assessment of smart structural systems

  • Hassan, Maguid H.M.
    • Structural Engineering and Mechanics
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    • 제23권5호
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    • pp.455-468
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    • 2006
  • Smart structural systems are defined as ones that demonstrate the ability to modify their characteristics and/or properties in order to respond favorably to unexpected severe loading conditions. The performance of such a task requires a set of additional components to be integrated within such systems. These components belong to three major categories, sensors, processors and actuators. It is wellknown that all structural systems entail some level of uncertainty, because of their extremely complex nature, lack of complete information, simplifications and modeling. Similarly, sensors, processors and actuators are expected to reflect a similar uncertain behavior. As it is imperative to be able to evaluate the impact of such components on the behavior of the system, it is as important to ensure, or at least evaluate, the reliability of such components. In this paper, a system model for reliability assessment of smart structural systems is outlined. The presented model is considered a necessary first step in the development of a reliability assessment algorithm for smart structural systems. The system model outlines the basic components of the system, in addition to, performance functions and inter-relations among individual components. A fault tree model is developed in order to aggregate the individual underlying component reliabilities into an overall system reliability measure. Identification of appropriate limit states for all underlying components are beyond the scope of this paper. However, it is the objective of this paper to set up the necessary framework for identifying such limit states. A sample model for a three-story single bay smart rigid frame, is developed in order to demonstrate the proposed framework.

Photon-counting linear discriminant analysis for face recognition at a distance

  • Yeom, Seok-Won
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제12권3호
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    • pp.250-255
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    • 2012
  • Face recognition has wide applications in security and surveillance systems as well as in robot vision and machine interfaces. Conventional challenges in face recognition include pose, illumination, and expression, and face recognition at a distance involves additional challenges because long-distance images are often degraded due to poor focusing and motion blurring. This study investigates the effectiveness of applying photon-counting linear discriminant analysis (Pc-LDA) to face recognition in harsh environments. A related technique, Fisher linear discriminant analysis, has been found to be optimal, but it often suffers from the singularity problem because the number of available training images is generally much smaller than the number of pixels. Pc-LDA, on the other hand, realizes the Fisher criterion in high-dimensional space without any dimensionality reduction. Therefore, it provides more invariant solutions to image recognition under distortion and degradation. Two decision rules are employed: one is based on Euclidean distance; the other, on normalized correlation. In the experiments, the asymptotic equivalence of the photon-counting method to the Fisher method is verified with simulated data. Degraded facial images are employed to demonstrate the robustness of the photon-counting classifier in harsh environments. Four types of blurring point spread functions are applied to the test images in order to simulate long-distance acquisition. The results are compared with those of conventional Eigen face and Fisher face methods. The results indicate that Pc-LDA is better than conventional facial recognition techniques.

A qualitative comparison study of information search behavior in online distribution

  • MIAO, Miao
    • 유통과학연구
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    • 제19권7호
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    • pp.61-73
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    • 2021
  • Purpose: This study offers suggestions to e-commerce companies for increasing shoppers' repurchase intention by considering the effect of distribution information in online shopping. It applies complexity theory to incorporate habitual information search behavior and shopper characteristics into the Stimulus-Organism-Response model and indicates how these complex factors work together in online shopping. Research design, data, and methodology: This study used an interview survey of 158 Vietnamese consumers with an experience of online shopping. A fuzzy-set Qualitative Comparative Analysis (fsQCA) was used to examine the relationship between antecedents and outcomes depending on complex conditions in the given contexts. Results: The results (1) indicate the importance of observing information search patterns and investigating their influence on online distribution, and (2) clarify what kind of configurations, under what conditions, predict a high or low outcome; this provides evidence and hints for the development of frameworks for future studies. Conclusions: The findings suggest that shoppers' unconscious, habitual behavior can work with conscious attitude factors, such as satisfaction, to increase their repurchase intention. Hence, e-commerce companies should consider how to present useful distribution information and create functions that allow shoppers to engage with a variety of information while increasing their repurchase intention on the site.