• 제목/요약/키워드: rule generation

검색결과 377건 처리시간 0.021초

규칙기반 온톨로지 자동생성 및 검색 (Ontology Generation and Information Retrieval using Rule-based Approach)

  • 윤현주;김영민;이상준;변영철
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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    • pp.655-657
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    • 2004
  • 본 논문에서는 특정 도메인에 대한 온톨로지를 규칙에 기반하여 자동으로 생성하고, 이를 기반으로 원하는 정보를 추론을 통하여 효과적으로 검색하는 방법에 대해 제안한다. 제안하는 방법이 실생활에 적용 할 수 있음을 보이기 위하며 실행과 관련된 정보중 숙박 정보를 담고 있는 HTML 웹 페이지를 테스트에 이용하였다. 웹 페이지에 표시되어 있는 숙박 정보에서 문서 구조 및 단어 측면에서의 규칙을 발견하고 이를 이용하여 온톨로지를 자동으로 생성한다. 숙박 정보 검색시 온톨로지에 정의된 관계를 이용하면 키워드는 다르더라도 동일한 의미를 갖는 다양한 키워드에 대한 효율적인 검색이 가능하다. 온톨로지 자동 생성을 통하여 기존 웹 페이지에 온톨로지 추가시 드는 시간 및 비용을 줄일 수 있으며, 온톨로지 기반 검색 방법을 이용함으로써 사용자에게 보다 양질의 정보를 제공할 수 있다.

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FNN에 기초한 Fuzzy Self-organizing Neural Network(FSONN)의 구조와 알고리즘의 구현 (The Implementation of the structure and algorithm of Fuzzy Self-organizing Neural Networks(FSONN) based on FNN)

  • 김동원;박병준;오성권
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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    • pp.114-117
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    • 2000
  • In this paper, Fuzzy Self-organizing Neural Networks(FSONN) based on Fuzzy Neural Networks(FNN) is proposed to overcome some problems, such as the conflict between ovefitting and good generation, and low reliability. The proposed FSONN consists of FNN and SONN. Here, FNN is used as the premise part of FSONN and SONN is the consequnt part of FSONN. The FUN plays the preceding role of FSONN. For the fuzzy reasoning and learning method in FNN, Simplified fuzzy reasoning and backpropagation learning rule are utilized. The number of layers and the number of nodes in each layers of SONN that is based on the GMDH method are not predetermined, unlike in the case of the popular multi layer perceptron structure and can be generated. Also the partial descriptions of nodes can use various forms such as linear, modified quadratic, cubic, high-order polynomial and so on. In this paper, the optimal design procedure of the proposed FSONN is shown in each step and performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

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적응하는 규책베이스의 생성 및 이의 동적 활용에 관한 연구 (A Study on Generation of Adaptive Rule Base and its Dynamic Application)

  • 조선영
    • 한국지능시스템학회논문지
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    • 제4권1호
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    • pp.50-63
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    • 1994
  • 기존의 지식 기반 시스템들은 그 지식의 형태를 대부분 규책을 통해서 처리하고 있다. 그리고 이런 규책들은 일반적으로 사람에 의해서 외부에서 주어진며 주어진 규칙은 학습이 진행됨에 따라 그 형태가 바뀌게 된다. 그러나 실생활에서 일어나는 대부분의 일들은 주어진 한정된 수의 규칙에 의해서만 수행되기보다는 반복수행 또는 점진적인 학습에 의해서 동적으로 그 수와 적용범위가 바뀌게 된다. 본 논문에서는 외부로부터 얻어지는 데이터를 통해서 그들 사이의 관계를 알아내고, 이를 통해 새로운 규칙을 생성하며, 계속적으로 학습이 진행됨에 따라서 능동적으로 규칙의 수와 적용범위가 변화하는 시스템을 제안한다. 동적 규칙 생성시스템의 유용성을 검증하기 위해서, 세 선분이 연결된 막대기의 한쪽 끝을 고정시킨 상태에서, 다른 쪽 끝이 원하는 위치에 도달하게 하는 문제에 적용하여 로보트 팔의 자동 조절 및 기계 학습의 자동화에 기여할 수 있음을 보여준다.

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연관분석을 이용한 마코프 논리네트워크의 1차 논리 공식 생성과 가중치 학습방법 (First-Order Logic Generation and Weight Learning Method in Markov Logic Network Using Association Analysis)

  • 안길승;허선
    • 산업경영시스템학회지
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    • 제38권1호
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    • pp.74-82
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    • 2015
  • Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

비젼 시스템에서 신경 회로망을 이용한 검사 영역에 관한 연구 (A study on inspection area using neural network for vision systems)

  • 오제휘;차영엽
    • 제어로봇시스템학회논문지
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    • 제4권3호
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    • pp.378-383
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    • 1998
  • A FOV, that stands for "Field Of View", refers to the maximum area where a camera could be wholly seen. If a FOV of CCD camera cannot the cover overall inspection area, the overall inspection area should be divided into sub-areas of size FOV. In this paper, we propose a new neural network-based FOV generation method by using a newly modified self-organizing map(SOM) which has multiple structure based on a self-organizing map, and uses new training rule that is composed of the movement, creation and deletion terms. Then, experiment results using real PCB indicate the superiority of the method developed in this study to the existing sequential method.al method.

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DESIGN AND IMPLEMENTATION OF THE ALL DIGITAL QPSK TRANSMITTER FOR MPEG-2 PACKETS SUPPORTING THE DAVIC STANDARD

  • Park, Sungsoo;Lee, Youngkou;Kim, Kiseon
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -2
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    • pp.914-918
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    • 2000
  • In this paper, a next generation high speed QPSK transmitter is designed based on 1.8${\mu}$m design rule. The designed transmitter supports the MPEG2-TS coded packed data for the DAVIC standard. Transmitter is composed of the convolutional coder, the shortened Reed-Solomon coder, and QPSK modulator. The coded packets are modulated in APSK with an RC filter. Especially, Galois Field multiplier with a standard basis is designed with the pipelined parallel architecture. Also, in the QPSK modulator, the RC filter and mixer are simplified into the ROM table, which can improve the performance of the transmitter. The total number of gates for the implemented baseband transmitter is 26,875.

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퍼지 규칙 생성에 의한 교환 시스템의 과부하 상태 검출 (Overload Detection in Switching Systems using FUzzy Rrules)

  • 주성순;이정훈
    • 전자공학회논문지C
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    • 제34C권6호
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    • pp.79-88
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    • 1997
  • New technologies, systems, and services in telecommunication have increased the need for an efficient and robust control mechanism to protect switching systems from overload. To achieve proper control, it is necessary to find a set of parameters that can describe the system. However, it is difficult to find types of data that can form a suitable basis for control. In this paper, we categorize the load status of a switching system into three classes (i.e., normal state, pre-overload state, and overload state) and formulate the overload detection as a classification problem. We find the relationships between the load classes and a set of monitored switching system parameters by applying a fuzzy rule-generation method. The rules are automatically generated from training data. Simulation results involving a switching system is given.

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AUTOMATIC TUNING OF FUZZY OPTIMAL CONTROL SYSTEM

  • Hoon-Kang;Lee, Hong-Gi-;Kim, Yong-Ho-;Jeon, Hong-Tae
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.1195-1198
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    • 1993
  • We investigate a systematic design procedure of automated rule generation of fuzzy logic based controller for uncertain dynamic systems such as an engine dynamic model.“Automated Tuning”means autonomous clustering or collection of such meaningful transitional relations in the state-space. Optimal control strategies are included in the design procedures, such as minimum squared error, minimum time, minimum energy or combined performance criteria. Fuzzy feedback control systems designed by the cell-state transition method have the properties of closed-loop stability, robustness under parameter variabtions, and a certain degree of optimality. Most of all, the main advantage of the proposed approach is that reliability can be potentially increased even if a large grain of uncertainty is involved within the control system under consideration. A numerical example is shown in which we apply our strategic fuzzy controller design to a highly nonlinear model of engine idle speed contr l.

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Type-2 FCM 기반 퍼지 추론 시스템의 설계 및 최적화 (Design of Type-2 FCM-based Fuzzy Inference Systems and Its Optimization)

  • 박건준;김용갑;오성권
    • 전기학회논문지
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    • 제60권11호
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    • pp.2157-2164
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    • 2011
  • In this paper, we introduce a new category of fuzzy inference system based on Type-2 fuzzy c-means clustering algorithm (T2FCM-based FIS). The premise part of the rules of the proposed model is realized with the aid of the scatter partition of input space generated by Type-2 FCM clustering algorithm. The number of the partition of input space is composed of the number of clusters and the individual partitioned spaces describe the fuzzy rules. Due to these characteristics, we can alleviate the problem of the curse of dimensionality. The consequence part of the rule is represented by polynomial functions with interval sets. To determine the structure and estimate the values of the parameters of Type-2 FCM-based FIS we consider the successive tuning method with generation-based evolution by means of real-coded genetic algorithms. The proposed model is evaluated with the use of numerical experimentation.

HCBKA 기반 IT2TSK 퍼지 예측시스템 설계 (Design of HCBKA-Based IT2TSK Fuzzy Prediction System)

  • 방영근;이철희
    • 전기학회논문지
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    • 제60권7호
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    • pp.1396-1403
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    • 2011
  • It is not easy to analyze the strong nonlinear time series and effectively design a good prediction system especially due to the difficulties in handling the potential uncertainty included in data and prediction method. To solve this problem, a new design method for fuzzy prediction system is suggested in this paper. The proposed method contains the followings as major parts ; the first-order difference detection to extract the stable information from the nonlinear characteristics of time series, the fuzzy rule generation based on the hierarchically classifying clustering technique to reduce incorrectness of the system parameter identification, and the IT2TSK fuzzy logic system to reasonably handle the potential uncertainty of the series. In addition, the design of the multiple predictors is considered to reflect sufficiently the diverse characteristics concealed in the series. Finally, computer simulations are performed to verify the performance and the effectiveness of the proposed prediction system.