• 제목/요약/키워드: inference operation

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퍼지추론 시스템을 이용한 지중송전계통 보호용 디지털 거리계전 알고리즘 개발 (Development of Digital Distance Relay Algorithm Using Fuzzy Inference System on Underground Power Cable Systems)

  • 정채균;이종범
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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    • pp.502-503
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    • 2006
  • If the fault occurs on the underground Power cable system, the fault current on the sheath has the influence on all sections because it's returned through earth at the directly grounded point and operation point of SVL(Sheath Voltage Limiter) at joint box. Therefore, the earth resistance and the operation of SVL have an effect on the zero-sequence current. Then the impedance between relaying point and fault point is Increased. That causes the overreach of distance relay. For these reasons, the distance relay algorithm for protecting of the underground power cable systems was developed. It effectively advance the errors using ACI(Advanced Computing Intelligence) technique. In this algorithm, the optimization was performed by fuzzy inference system and genetic algorithm.

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ON APPROXIMATION OF CONTROLS BY FUZZY SYSTEMS

  • Nguyen, Hung T.;Kreinovich, Vladik
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1414-1417
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    • 1993
  • Wang and Medel proved (1991) that fuzzy systems with product inference, centroid defuzzification, and everywhere positive membership functions (in particular, Gaussians, Wang, 1992) are capable of approximating any real continuous control function on a compact set to arbitrary accuracy. Kosko (1992) proved that fuzzy systems, in which membership functions have compact support, and combination operation (V-operation) for rules is the sum, are also universal approximators. In this paper, we generalize this result of Kosko and prove that for any &- and V-operations, any defuzzification procedure, and any basic membership function with a compact support, the resulting fuzzy controls are universal approximators. Also, Wang's result is transfered to min-inference.

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KubEVC-Agent : 머신러닝 추론 엣지 컴퓨팅 클러스터 관리 자동화 시스템 (KubEVC-Agent : Kubernetes Edge Vision Cluster Agent for Optimal DNN Inference and Operation)

  • 송무현;김규민;문지훈;김유림;남채원;박종빈;이경용
    • 대한임베디드공학회논문지
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    • 제18권6호
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    • pp.293-301
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    • 2023
  • With the advancement of artificial intelligence and its various use cases, accessing it through edge computing environments is gaining traction. However, due to the nature of edge computing environments, efficient management and optimization of clusters distributed in different geographical locations is considered a major challenge. To address these issues, this paper proposes a centralization and automation tool called KubEVC-Agent based on Kubernetes. KubEVC-Agent centralizes the deployment, operation, and management of edge clusters and presents a use case of the data transformation for optimizing intra-cluster communication. This paper describes the components of KubEVC-Agent, its working principle, and experimental results to verify its effectiveness.

Spring Flow Prediction affected by Hydro-power Station Discharge using the Dynamic Neuro-Fuzzy Local Modeling System

  • Hong, Timothy Yoon-Seok;White, Paul Albert.
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2007년도 학술발표회 논문집
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    • pp.58-66
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    • 2007
  • This paper introduces the new generic dynamic neuro-fuzzy local modeling system (DNFLMS) that is based on a dynamic Takagi-Sugeno (TS) type fuzzy inference system for complex dynamic hydrological modeling tasks. The proposed DNFLMS applies a local generalization principle and an one-pass training procedure by using the evolving clustering method to create and update fuzzy local models dynamically and the extended Kalman filtering learning algorithm to optimize the parameters of the consequence part of fuzzy local models. The proposed DNFLMS is applied to develop the inference model to forecast the flow of Waikoropupu Springs, located in the Takaka Valley, South Island, New Zealand, and the influence of the operation of the 32 Megawatts Cobb hydropower station on springs flow. It is demonstrated that the proposed DNFLMS is superior in terms of model accuracy, model complexity, and computational efficiency when compared with a multi-layer perceptron trained with the back propagation learning algorithm and well-known adaptive neural-fuzzy inference system, both of which adopt global generalization.

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Moving Object Management System for Battlefield Simulation

  • Ahn, Yoon-Ae
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.663-675
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    • 2004
  • A battlefield simulation is the evaluation and analysis of the battlefield area, based on the data for terrain, climate, unit's maneuver and tactics basically required in battlefield simulation. Because it is difficult for the military authorities to collect all of the information perfectly for the reason of communication technology, jamming, and tactics, the military authorities need the future moving status for the target units by using acquired moving information. Therefore, we propose a moving object management system that concurrently provides domain reasoning function for the battlefield simulation. In order to implement the proposed system, we show the data modeling of the moving object for the battlefield simulation, and propose an inference engine using domain rule base and spatiotemporal operation. Also, we analyze the query response rate by inference function to verify domain reasoning of the implemented system.

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A Multiple-Valued Fuzzy Approximate Analogical-Reasoning System

  • Turksen, I.B.;Guo, L.Z.;Smith, K.C.
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1274-1276
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    • 1993
  • We have designed a multiple-valued fuzzy Approximate Analogical-Reseaning system (AARS). The system uses a similarity measure of fuzzy sets and a threshold of similarity ST to determine whether a rule should be fired, with a Modification Function inferred from the Similarity Measure to deduce a consequent. Multiple-valued basic fuzzy blocks are used to construct the system. A description of the system is presented to illustrate the operation of the schema. The results of simulations show that the system can perform about 3.5 x 106 inferences per second. Finally, we compare the system with Yamakawa's chip which is based on the Compositional Rule of Inference (CRI) with Mamdani's implication.

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베이지안 추론법을 이용한 교량 운영단계에서의 예방적 유지관리 전략 (The Preventive Maintenance Strategy in Operation Stage of Bridge using Bayesian Inference)

  • 이진혁;최양록;안호준;공정식
    • 대한토목학회논문집
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    • 제39권1호
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    • pp.135-146
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    • 2019
  • 본 논문에서는 베이지안 추론법을 이용한 교량 실제 운영단계에서의 예방적 유지관리 전략 수립 기법을 제안하였다. 제안된 기법은 모니터링의 불확실성을 고려하여 실제 대상 교량의 상태 변화를 높은 확률로 예측할 수 있다. 실제 공용 중인 교량에 제안된 기법의 적용성을 검토함과 동시에, 손상이 발현된 후 유지보수 조치계획을 수립하는 현행 유지관리체계와 비교하여 유지관리 비용 효율성 측면에서 유리함을 분석하였다. 제안된 기법을 이용하여 기존 유지관리방법의 한계를 극복하고, 공용 중인 교량의 실질적인 유지관리체계 수립을 위한 교량 유지관리 의사결정에 활용할 수 있을 것으로 기대한다.

A Fuzzy Inference based Reliability Method for Underground Gas Pipelines in the Presence of Corrosion Defects

  • 김성준;최병학;김우식;김익중
    • 한국지능시스템학회논문지
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    • 제26권5호
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    • pp.343-350
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    • 2016
  • Remaining lifetime prediction of the underground gas pipeline plays a key role in maintenance planning and public safety. One of main causes in the pipeline failure is metal corrosion. This paper deals with estimating the pipeline reliability in the presence of corrosion defects. Because a pipeline has uncertainty and variability in its operation, probabilistic approximation approaches such as first order second moment (FOSM), first order reliability method (FORM), second order reliability method (SORM), and Monte Carlo simulation (MCS) are widely employed for pipeline reliability predictions. This paper presents a fuzzy inference based reliability method (FIRM). Compared with existing methods, a distinction of our method is to incorporate a fuzzy inference into quantifying degrees of variability in corrosion defects. As metal corrosion depends on the service environment, this feature makes it easier to obtain practical predictions. Numerical experiments are conducted by using a field dataset. The result indicates that the proposed method works well and, in particular, it provides more advisory estimations of the remaining lifetime of the gas pipeline.

도착 및 이탈시점을 이용한 다중서버 대기행렬 추론 (An Inference Method of a Multi-server Queue using Arrival and Departure Times)

  • 박진수
    • 한국시뮬레이션학회논문지
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    • 제25권3호
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    • pp.117-123
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    • 2016
  • 본 연구는 다중서버 대기행렬시스템의 관측이 제한되어 있는 경우에 시스템 내부 행태를 추론하는 데에 그 목적이 있다. 대기행렬시스템 분석에 있어 도착 및 서비스시간에 자기상관성이 존재하면 이론적으로 모형화하기가 매우 복잡하고 어렵다. 이에 따라 다양한 분석 기법 및 확률과정 모형들이 개발되었다. 본 논문에서는 외부 관측치에 존재하는 자기상관성과 내부 행태를 관측하기 어려운 경우에 대한 추론 방법을 소개한다. 선행연구의 가정을 완화하여 추론 방법을 제시하고 그에 대한 보조정리 및 정리를 제시한다. 제시된 비모수적 방법을 적용하면 서비스시간에 자기상관성이 존재하더라도 외부 관측치만을 사용하여 다중서버 대기행렬의 내부 행태를 추론할 수 있다. 주요 내부 추론 결과로는 대기시간과 서비스시간을 사용하였다. 또한 제시된 방법의 타당성 검증을 위해 실험 결과를 제시하였다.

차세대 웹을 위한 SWRL 기반 역방향 추론엔진 SMART-B의 개발 (Development of an SWRL-based Backward Chaining Inference Engine SMART-B for the Next Generation Web)

  • 송용욱;홍준석;김우주;윤숙희;이성규
    • 지능정보연구
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    • 제12권2호
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    • pp.67-81
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    • 2006
  • 현재의 웹이 HTML을 바탕으로 인간 사용자와의 인터페이스에 초점을 맞추고 있는데 비하여, 차세대 웹은 XML 및 XML 기반 각종 표준들을 바탕으로 소프트웨어 에이전트간의 상호작용에 초점을 맞추어 나가고 있다. 차세대 웹에서 소프트웨어 에이전트의 두뇌 역할을 수행하기 위하여 추론엔진은 차세대 웹의 표준 언어인 시맨틱 웹 - (Semantic Web)을 충실히 이해할 수 있어야 한다. 이를 위한 기초 작업의 일환으로 OWL(Web Ontology Language) 과 RuleML(Rule Markup Language)을 조합한 SWRL(Semantic Web Rule Language)이 W3C에 제안된 바 있다. 본 연구에서는 SWRL을 규칙 표현 방법으로 사용하고, OWL을 사실 표현 방법으로 사용하는 역방향 추론엔진인 SMART-B(SeMantic web Agent Reasoning Tools -Backward chaining inference engine)를 개발하고자 하였다. 이를 위하여 SWRL 기반 역방향 추론을 위한 요구 기능을 분석하고, 기존 역방향 추론 알고리즘에 차세대 시맨틱 웹의 요구 기능을 반영한 역방향 추론 알고리즘을 설계하였다. 또한, 유비쿼터스 환경에서의 각종 플랫폼간의 독립성과 이식성을 확보하고 기기간의 성능 차이를 극복할 수 있도록 사실 베이스 및 규칙 베이스의 관리도구와 역방향 추론 엔진 등을 Java 프로그래밍 언어를 이용하여 단위 컴포넌트의 형태로 개발하였다.

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