• 제목/요약/키워드: Inference function

검색결과 450건 처리시간 0.024초

동적환경에서 퍼지추론을 이용한 이동로봇의 다중센서기반의 자율주행 (Multisensor-Based Navigation of a Mobile Robot Using a Fuzzy Inference in Dynamic Environments)

  • 진태석;이장명
    • 한국정밀공학회지
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    • 제20권11호
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    • pp.79-90
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    • 2003
  • In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

퍼지 활성 노드를 가진 퍼지 다항식 뉴럴 네트워크 (Fuzzy Polynomial Neural Networks with Fuzzy Activation Node)

  • 박호성;김동원;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 D
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    • pp.2946-2948
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    • 2000
  • In this paper, we proposed the Fuzzy Polynomial Neural Networks(FPNN) model with fuzzy activation node. The proposed FPNN structure is generated from the mutual combination of PNN(Polynomial Neural Networks) structure and fuzzy inference system. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. The structure of FPNN is not fixed like in conventional Neural Networks and can be generated. The design procedure to obtain an optimal model structure utilizing FPNN algorithm is shown in each stage. Gas furnace time series data used to evaluate the performance of our proposed model.

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퍼지 추론을 이용한 적응적 DC/AC 인버터 설계 (Adaptive DC to AC Invertor Design based on Fuzzy Inference for Power Consumption monitoring)

  • 김윤호
    • 한국정보통신학회논문지
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    • 제7권7호
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    • pp.1520-1526
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    • 2003
  • 본 논문에서는 마이크로프로세서를 이용하여 소비전력 모니터링이 가능한 100[W]급 직류입력/교류출력변환 인버터를 설계하였다. 또한 입출력 제어와 소비전력정보 모니터링을 외부환경에 적응적으로 대응하기 위해 퍼지추론 시스템을 설계하였다. 추론결과를 PIC16C711 프로세서에서 처리함으로서 입력전압의 변화와 소자의 온도특성 등에 적응적인 인버터 설계가 가능함을 보였다. 제작된 시스템을 이용하여 효율실험 및 부하실험을 수행하였고 오차는 2% 이내임을 확인하였다.

농업용 필댐의 안전진단등급 평가법 개선을 위한 퍼지논리 적용법 개발 (A Development of Fuzzy-Logic Application for Improving Safety Diagnosis Rating Method of Agricultural Fill Dam)

  • 윤성욱;유찬
    • 한국농공학회논문집
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    • 제65권4호
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    • pp.33-43
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    • 2023
  • In this study, it was developed and verified an application method of fuzzy-logic theory to the rating process of agricultural fill dam safety. A fuzzy-logic is very famous logical system when some decision making is made on the status of a lack of information. Three proxies were selected and configured membership functions (MFs) and these MFs were activated in the process of fuzzification procedures. Fuzzified vlaues were passed through the rule-based inference system, then fire strength could classified among cases of the rule-based inference system. To obtain final results, Mandani-type was adapted in the defuzzification process. As the results, it was shown the developed system can give a correct results that was compared with Matlab - fuzzy inference function. More ever it could perform the detailed analysis and improvement on the infrastructure safety rating process using classical diagnosis method.

Applications of Soft Computing Techniques in Response Surface Based Approximate Optimization

  • Lee, Jongsoo;Kim, Seungjin
    • Journal of Mechanical Science and Technology
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    • 제15권8호
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    • pp.1132-1142
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    • 2001
  • The paper describes the construction of global function approximation models for use in design optimization via global search techniques such as genetic algorithms. Two different approximation methods referred to as evolutionary fuzzy modeling (EFM) and neuro-fuzzy modeling (NFM) are implemented in the context of global approximate optimization. EFM and NFM are based on soft computing paradigms utilizing fuzzy systems, neural networks and evolutionary computing techniques. Such approximation methods may have their promising characteristics in a case where the training data is not sufficiently provided or uncertain information may be included in design process. Fuzzy inference system is the central system for of identifying the input/output relationship in both methods. The paper introduces the general procedures including fuzzy rule generation, membership function selection and inference process for EFM and NFM, and presents their generalization capabilities in terms of a number of fuzzy rules and training data with application to a three-bar truss optimization.

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Automatic Log-in System by the Speaker Certification

  • Sohn, Young-Sun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제4권2호
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    • pp.176-181
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    • 2004
  • This paper introduces a Web site login system that uses user's native voice to improve the bother of remembering the ID and password in order to login the Web site. The DTW method that applies fuzzy inference is used as the speaker recognition algorithm. We get the ACC(Average Cepstrum Coefficient) membership function by each degree, by using the LPC that models the vocal chords, to block the recorded voice that is problem for the speaker recognition. We infer the existence of the recorded voice by setting on the basis of the number of zeros that is the value of the ACC membership function, and on the basis of the average value of the ACC membership function. We experiment the six Web sites for the six subjects and get the result that protects the recorded voice about 98% that is recorded by the digital recorder.

Initial Mass Function and Star Formation History in the Small Magellanic Cloud

  • Lee, Ki-Won
    • 한국지구과학회지
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    • 제35권5호
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    • pp.362-374
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    • 2014
  • This study investigated the initial mass function (IMF) and star formation history of high-mass stars in the Small Magellanic Cloud (SMC) using a population synthesis technique. We used the photometric survey catalog of Lee (2013) as the observable quantities and compare them with those of synthetic populations based on Bayesian inference. For the IMF slope (${\Gamma}$) range of -1.1 to -3.5 with steps of 0.1, five types of star formation models were tested: 1) continuous; 2) single burst at 10 Myr; 3) single burst at 60 Myr; 4) double bursts at those epochs; and 5) a complex hybrid model. In this study, a total of 125 models were tested. Based on the model calculations, it was found that the continuous model could simulate the high-mass stars of the SMC and that its IMF slope was -1.6 which is slightly steeper than Salpeter's IMF, i.e., ${\Gamma}=-1.35$.

졸음운전 방지를 위한 fuzzy 추론에 의한 각성도의 평가 (Evaluation of Arousal Level to Prevent Drowsy Driving by Fuzzy Inference)

  • 김연호;고한우;유준
    • 대한의용생체공학회:의공학회지
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    • 제18권4호
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    • pp.491-498
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    • 1997
  • 본 연구에서는 졸음운전 방지를 위한 방법으로 기존의 3단계 경고음법과 fuzzy logic을 이용한 가성도 측정 및 제어법을 시뮬레이션으로 비교 및 분석하였다. 각성상태를 제어하는 방법으로 사용되었던 기존의 각성제어지표는 실 차에는 사용될 경우 효과적이지 못하므로 각성상태에 따른 영역별 Nz와 IRI의 상관분포도를 분석하여 기존의 각성제어지표를 수정하였다. Fuzzy 추론으로는 Sugeno의 방법을 사용하였고 멤버쉽함수와 제어규칙 베이스는 수정된 각성제어지표로부터 결정하였다. 시뮬레이션 결과 60이하의 IRI가 발생되는 경우, Nz의 변화에 따라 두 제어방법 모두 small, medium, big의 경고음이 발생되었으나 3단계 경고음법은 다음 단계의 발생영역이 될 때까지 같은 출력만을 발생한다. 그러나 퍼지추론의 출력은 피검자의 각성수준의 변화에 잘 추종하여 변화되었으므로 3단계 경고음법의 문제점을 해겨할 수 있었고 더욱이 퍼지 추론의 출력과 Nz와의 상관계수(r=0.99)가 매우 높았으므로, 실제 운전시 퍼지추론 방법을 이용한 각성도 평가 및 제어에 적용할 경우 3단계 경고음법 보다 효과적일 것으로 기대된다.

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Ubiquitous Architectural Framework for UbiSAS using Context Adaptive Rule Inference Engine

  • Yoo, Yoon-Sik;Huh, Jae-Doo
    • 한국정보기술응용학회:학술대회논문집
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    • 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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    • pp.243-246
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    • 2005
  • Recent ubiquitous computing environments increasingly impact on our lives using the current technologies of sensor network and ubiquitous services. In this paper, we propose ubiquitous architectural framework for ubiquitous sleep aid service(UbiSAS) in the subset of ubiquitous computing for refreshing of human's sleep. And we examine technical feasibility. Human can recover his health through refreshing sleep from fatigue. Ubiquitous architectural framework for UbiSAS in digital home offers agreeable sleeping environment and improves recovery from fatigue. So we present new concept of ubiquitous architectural framework dissolving stress. Specially, we apply context to context-aware framework module. This context is transferred to context adaptive inference engine which has service invocation function in intelligent agent module. Ubiquitous architectural framework for UbiSAS using context adaptive rule inference engine without user intervention is technical issue. That is to say, we should take sleep comfortably during our sleeping. And sensed information during sleeping is changed to context-aware information. This presents significant information in context adaptive rule inference engine for UbiSAS. This information includes all sleeping state during sleeping in context-aware computing technique. So we propose more effective and most suitable ubiquitous architectural framework using context adaptive rule inference engine for refreshing sleep in this paper.

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