• Title/Summary/Keyword: 퍼지공간관계

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Fuzzy Quantization and Rate Control for Very Low Bit­rate Video Coder (초저전송율 동영상 부호기를 위한 퍼지 양자화 및 율 제어에 관한 연구)

  • 양근호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.8
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    • pp.1684-1690
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    • 2003
  • In this paper, we proposed a fuzzy controller for the evaluation of the quantization Parameters in the H.263 coder to optimize the subjective quality of each coded frame, keeping the transmission rate constant. We adopted the Mamdani method for fuzzification and the centroid method for defuzzification. The energy and entropy are correlated to features of the HVS in spatial domain, while motion vectors are used to estimate the temporal characteristics of the signal. And then, the fuzzy inputs adapted the variance and the entropy in spatial domain, and the motion vector in temporal domain. We induced the fuzzy membership function and decided the fuzzy relevance to be compatible in visual characteristics. And then, we designed FAM banks. The fuzzy technology has been applied to a practical video compression. This results is obtained an effective rate control technique, an optimum bit allocation and a high subjective quality using fuzzy quantization.

GIS-based Data-driven Geological Data Integration using Fuzzy Logic: Theory and Application (퍼지 이론을 이용한 GIS기반 자료유도형 지질자료 통합의 이론과 응용)

  • ;;Chang-Jo F. Chung
    • Economic and Environmental Geology
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    • v.36 no.3
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    • pp.243-255
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    • 2003
  • The mathematical models for GIS-based spatial data integration have been developed for geological applications such as mineral potential mapping or landslide susceptibility analysis. Among various models, the effectiveness of fuzzy logic based integration of multiple sets of geological data is investigated and discussed. Unlike a traditional target-driven fuzzy integration approach, we propose a data-driven approach that is derived from statistical relationships between the integration target and related spatial geological data. The proposed approach consists of four analytical steps; data representation, fuzzy combination, defuzzification and validation. For data representation, the fuzzy membership functions based on the likelihood ratio functions are proposed. To integrate them, the fuzzy inference network is designed that can combine a variety of different fuzzy operators. Defuzzification is carried out to effectively visualize the relative possibility levels from the integrated results. Finally, a validation approach based on the spatial partitioning of integration targets is proposed to quantitatively compare various fuzzy integration maps and obtain a meaningful interpretation with respect to future events. The effectiveness and some suggestions of the schemes proposed here are illustrated by describing a case study for landslide susceptibility analysis. The case study demonstrates that the proposed schemes can effectively identify areas that are susceptible to landslides and ${\gamma}$ operator shows the better prediction power than the results using max and min operators from the validation procedure.

Fuzzy Approach of Learning Evaluation Model in Intelligent E-Learning Systems (지능형 가상 학습 시스템에서 학습 평가 모델의 퍼지적 접근)

  • Weon, Sung Hyun
    • The Journal of Korean Association of Computer Education
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    • v.8 no.1
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    • pp.55-63
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    • 2005
  • Recently, web-based E-learning systems have entered the spotlight by providing new learning environments that break down spatial and temporal limitations. The key to building the web-based E-learning system is in determining how to effectively use the system and to evaluate the degree of learning achieved by the students that use it. In traditional off-line learning systems, we can evaluate students by counting how many questions, designed to evaluate their learning achievement, he or she answers correctly within a predetermined time limit. But this method would make individualized learning, a strong point of E-learning systems, impossible because these systems provide same learning strategy to all students even though they achieve a different level of learning. Therefore, in this paper, I will find any relationships between given test answers using fuzzy implication theory, I call these fuzzy correlations, and then generate evaluation results that are reflected in those relationships. I will compare the differences between this evaluation method and a traditional evaluation method where a student takes a test to evaluate his or her learning achievement after some learning period. Finally, I will discuss how we can use these results in individualized learning.

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The Design of Genetic Fuzzy Set Polynomial Neural networks based on Information Granules and Its Application of Multi -variables System (정보 입자 기반 유전론적 퍼지 집합 다항식 뉴럴네트워크 설계와 다변수 시스템으로의 응용)

  • Lee In-Tae;Oh Sung-Kwun;Kim Hyun-Ki;Seo Ki-Sung
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.11a
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    • pp.479-482
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    • 2005
  • 본 논문에서는 퍼지 뉴럴네트워크의 새로운 구조인 Fuzzy Set-based Polynomial Neural Networks(FSPNN)을 소개한다. 제안된 모델은 일반적인 최적화 방법과 정보 입자를 이용하여 네트워크를 설계한다. 최종 구조는 Fuzzy Set-based Polynomial Neuron(FSPN)을 기반으로 설계한 FPNN과 동일하다. 첫째로 FSPNS의 종합적인 설계방법(유전자 알고리즘을 이용한 최적 구조 탐색)에 대해 소개한다. FSPNN에 관계되는 입력변수의 개수, 후반부 다항식의 차수, 멤버쉽 함수의 수 그리고 입력변수 개수에 따른 입력변수를 유전자 알고리즘을 통하여 동조한다. 두 번째로, 입력 변수의 개별적인 퍼지 규칙 형성과 퍼지 공간 분할 및 삼각형 멤버쉽 함수의 초기 정점을 HCM 클러스터링을 통한 Information Granules로 정의한다. 또한 데이터 입자의 중심을 이용하여 후반부의 구조를 결정한다. 이 네트워크의 성능은 기존에 퍼지 또는 뉴로퍼지 모델링에서 실험된 모델링 표준치를 이용하여 평가한다.

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A Restriction Strategy for Automated Reasoning using a Fuzzy Algorithm (퍼지 알고리즘을 이용한 자동화된 추론의 입력 제한 기법)

  • Kim, Yong-Gi;Baek, Byeong-Gi;Gang, Seong-Su
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.4
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    • pp.1025-1034
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    • 1997
  • Inference process of resolution-based automated reasoning easily consumes the memory of computer without giving any useful result by priducing lots of fruioless information which are not necessary for the conslusion. This paper suggests a control strategy for saving the space of computer memory and reducing the inference time. The strategy uses a restriction that comparatively irrelevant axioms do mot take pare in the resoluition. In order to analyze and determine the priorities of the input axioms of joning the inference process, the system employs the fuzzy relational products.

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Image Retrieval with Fuzzy Triples to Support Inexact and Concept-based Match (근사 정합과 개념 기반 정합을 지원하는 퍼지 트리플 기반 이미지 검색)

  • Jeong, Seon-Ho;Yang, Jae-Dong;Yang, Hyeong-Jeong
    • Journal of KIISE:Software and Applications
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    • v.26 no.8
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    • pp.964-973
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    • 1999
  • 본 논문에서는 퍼지 트리플을 사용하는 내용 기반 이미지 검색 방법을 제안한다. 이미지 내 객체들 사이의 공간 관계는 내용 기반 이미지 검색을 위해 사용되는 주요한 속성들 중의 하나이다. 그러나, 기존의 트리플을 이용한 이미지 검색 시스템들은 개념 기반 검색 방법을 지원하지 못하고, 방향들 사이의 근사 정합을 처리하지 못하는 문제점을 가지고 있다. 이 문제를 해결하기 위하여 본 논문에서는 개념 기반 정합과 근사 정합을 지원하는 퍼지 트리플을 이용한 이미지 검색 방법을 제안한다. 개념 기반 정합을 위해서는 퍼지 소속성 집합으로 이루어진 시소러스가 사용되며, 근사 정합을 위해서는 방향들 사이의 관계를 정량화 하기 위한 k-weight 함수가 각각 이용된다. 이 두 가지 정합은 퍼지 트리플 간의 퍼지 정합을 통하여 균일하게 지원될 수 있다. 본 논문에서는 또한, 개념 기반 정합과 근사 정합에 대한 검색 효과를 정량적으로 평가하는 작업을 수행한다. Abstract This paper proposes an inexact and a concept-based image match technique based on fuzzy triples. The most general method adopted to index and retrieve images based on this spatial structure may be triple framework. However, there are two significant drawbacks in this framework; one is that it can not support a concept-based image retrieval and the other is that it fails to deal with an inexact match among directions. To compensate these problems, we develope an image retrieval technique based on fuzzy triples to make the inexact and concept-based match possible. For the concept-based match, we employ a set of fuzzy membership functions structured like a thesaurus, whereas for the inexact match, we introduce k-weight functions to quantify the similarity between directions. In fuzzy triples, the two facilities are uniformly supported by fuzzy matching. In addition, we analyze the retrieval effectiveness of our framework regarding the degree of the conceptual matching and the inexact matching.

A Design of GA-based TSK Fuzzy Classifier and Its Application (GA 기반 TSK 퍼지 분류기의 설계와 응용)

  • 곽근창;김승석;유정웅;김승석
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.8
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    • pp.754-759
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    • 2001
  • In this paper, we propose a TSK(Takagi-Sugeno-Kang)-type fuzzy classifier using PCA(Principal Component Analysis), FCM(Fuzzy c-Means) clustering, ANFIS(Adaptive Neuro-Fuzzy Inference System) and hybrid GA(Genetic Algorithm). First, input data is transformed to reduce correlation among the data components by PCA. FCM clustering is applied to obtain a initial TSK-type fuzzy classifier. Parameter identification is performed by AGA(Adaptive GA) and RLSE(Recursive Least Square Estimate). Finally, we applied the proposed method to Iris data classificationl problems and obtained a better performance than previous works.

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An Investigation of Technical Methods to Solve the Internet Negative-Function (인터넷 역기능을 해결키 위한 기술적 방법론에 대한 검토)

  • 조동욱;신승수
    • The Journal of the Korea Contents Association
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    • v.2 no.4
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    • pp.40-45
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    • 2002
  • The network community provides people a new area which is called a cyber area, not physical area. However, today in the cyber area, the negative function has been causing social problem. In fact, it has not been causing by original function. Specifically speaking, main reason why it's leading to the negative function is that teenagers are logging into inappropriate sites (such as: violent, adult sites) to unnecessary sites (such as: e-mails with unknown signs combined with words, inappropriate language used in certain web board). Not only that, private password and ID's are being used by unknown user to accomplish illegal access. If this problem does not get solved through immediate development of technologies method, the cyber crime will increase in short period of time. The purpose of this paper is to understand each analyzed method which can cope with negative internet function, to discuss suitable management in certain web board an to check with fuzzy intercommunication mood.

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Effective Recognition of Land Registration Map Using Fuzzy Inference (퍼지추론 기반의 효율적인 지적도면 인식)

  • Kim, Yoon-Ho
    • Journal of Advanced Navigation Technology
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    • v.11 no.3
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    • pp.343-349
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    • 2007
  • This paper addressed a recognition method of land registration map based on fuzzy inference scheme, which is able to solve the time complexity problem of typical method [Fig. 2]. Not only line color, thickness but also number, character are used as a fuzzy input parameter. It concentrated on generation of fuzzy association map, and useful informations are extracted result from fuzzy inference. These results are precedent process for estimating the construction space and restoring 3D automatic modeling. It can also utilize to the internet service acceleration propulsion business such as u-Gov based land registration service.

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Fuzzy Model-Based Emotion Recognition Using Color Image (퍼지 모델을 기반으로 한 컬러 영상에서의 감성 인식)

  • Joo, Young-Hoon;Jeong, Keun-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.3
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    • pp.330-335
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    • 2004
  • In this paper, we propose the technique for recognizing the human emotion by using the color image. To do so, we first extract the skin color region from the color image by using HSI model. Second, we extract the face region from the color image by using Eigenface technique. Third, we find the man's feature points(eyebrows, eye, nose, mouse) from the face image and make the fuzzy model for recognizing the human emotions (surprise, anger, happiness, sadness) from the structural correlation of man's feature points. And then, we infer the human emotion from the fuzzy model. Finally, we have proven the effectiveness of the proposed method through the experimentation.