• Title/Summary/Keyword: Fuzzy Relational Theory

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Implementation issues for Uncertain Relational Databases

  • Yu, Hairong;Ramer, Arthur
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.128-133
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    • 1998
  • This paper aims to present some ideas for implementation of Uncertain Relational Databases (URD) which are extensions of classical relational databases. Our system firstly is based on possibility distribution and probability theory to represent and manipulate fuzzy and probabilistic information, secondly adopts flexible mechanisms that allow the management of uncertain data through the resources provided by both available relational database management systems and front-end interfaces, and lastly chooses dynamic SQL to enhance versatility and adjustability of systems.

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Extraction of Fuzzy Rules from Data using Rough Set (Rough Set을 이용한 퍼지 규칙의 생성)

  • 조영완;노흥식;위성윤;이희진;박민용
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.327-332
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    • 1996
  • Rough Set theory suggested by Pawlak has a property that it can describe the degree of relation between condition and decision attributes of data which don't have linguistic information. In this paper, by using this ability of rough set theory, we define a occupancy degree which is a measure can represent a degree of relational quantity between condition and decision attributes of data table. We also propose a method that can find an optimal fuzzy rule table and membership functions of input and output variables from data without linguistic information and examine the validity of the method by modeling data generated by fuzzy rule.

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A Study of the Effective Method for Collecting and Analyzing Human Sensibility Applied Fuzzy Set Theory (퍼지이론을 응용한 효율적 감성 수집과 분석에 관한 연구)

  • Baek, Seung-Ryeol;Park, Beom
    • Journal of the Ergonomics Society of Korea
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    • v.17 no.1
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    • pp.47-54
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    • 1998
  • Product design and development is very important process in enterprise activities. Reducing development time and reflecting consumer's needs is required to product design and development for increasing benefit and decreasing cost. Human sensibility ergonomics is one of the important technology of R&D in product development. However, the subjective method of human sensibility ergonomics has several problems to analyze and to Quantify experimental data and objective method of human sensibility ergonomics is still in process on study. In this research, new analyzing method is proposed for the subjective human sensibility ergonomics applied with fuzzy set theory. What is the useful theory for controlling uncertain type of information like human mind? This approach is more effective method for analyzing consumer's needs for product design and development process. At collecting needs, certainty scale is added for adapting hedge of fuzzy function. Using a kind of union operator, synthesize each item to analyze identification of each item with fuzzy hamming distance. Identification of analysis is classified with the relational weight using Relationship Chart Method, and is drawn the relationship diagram for clustering each item. A case study with sample test is conducted and demonstrated with this suggested method for more effective way.

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Different approaches towards fuzzy database systems A Survey

  • Rundensteiner, Elke A.;Hawkes, Lois Wright
    • Journal of the Korean Institute of Intelligent Systems
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    • v.3 no.1
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    • pp.65-75
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    • 1993
  • Fuzzy data is a phenomenon often occurring in real life. There is the inherent vagueness of classification terms referring to a continuous scale, the uncertainty of linguistic terms such as "I almost agree" or the vagueness of terms and concepts due to the statistical variability in communication [20] and many more. Previously, such fuzzy data was approximated by non-fuzzy (crisp) data, which obviously did not lead to a correct and precise representation of the real world. Fuzzy set theory has been developed to represent and manipulate fuzzy data [18]. Explicitly managing the degree of fuzziness in databases allows the system to distinguish between what is known, what is not known and what is partially known. Systems in the literature whose specific objective is to handle imprecision in databases present various approaches. This paper is concerned with the different ways uncertainty and imprecision are handled in database design. It outlines the major areas of fuzzification in (relational) database systems.

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Elicitation of Collective Intelligence by Fuzzy Relational Methodology (퍼지관계 이론에 의한 집단지성의 도출)

  • Joo, Young-Do
    • Journal of Intelligence and Information Systems
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    • v.17 no.1
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    • pp.17-35
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    • 2011
  • The collective intelligence is a common-based production by the collaboration and competition of many peer individuals. In other words, it is the aggregation of individual intelligence to lead the wisdom of crowd. Recently, the utilization of the collective intelligence has become one of the emerging research areas, since it has been adopted as an important principle of web 2.0 to aim openness, sharing and participation. This paper introduces an approach to seek the collective intelligence by cognition of the relation and interaction among individual participants. It describes a methodology well-suited to evaluate individual intelligence in information retrieval and classification as an application field. The research investigates how to derive and represent such cognitive intelligence from individuals through the application of fuzzy relational theory to personal construct theory and knowledge grid technique. Crucial to this research is to implement formally and process interpretatively the cognitive knowledge of participants who makes the mutual relation and social interaction. What is needed is a technique to analyze cognitive intelligence structure in the form of Hasse diagram, which is an instantiation of this perceptive intelligence of human beings. The search for the collective intelligence requires a theory of similarity to deal with underlying problems; clustering of social subgroups of individuals through identification of individual intelligence and commonality among intelligence and then elicitation of collective intelligence to aggregate the congruence or sharing of all the participants of the entire group. Unlike standard approaches to similarity based on statistical techniques, the method presented employs a theory of fuzzy relational products with the related computational procedures to cover issues of similarity and dissimilarity.

Intelligent System Design for Knowledge Representation and Interpretation of Human Cognition (인간 인지 지식의 표현과 해석을 위한 지능형 시스템 설계 방법)

  • Joo, Young-Do
    • Journal of Korea Society of Industrial Information Systems
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    • v.16 no.3
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    • pp.11-21
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    • 2011
  • The development of computer-based modeling system has allowed the operationalization of cognitive science issues. Human cognition has become one of most interesting research subjects in artificial intelligence to emulate human mentality and behavior. This paper introduces a methodology well-suited for designing the intelligent system of human cognition. The research investigates how to elicit and represent cognitive knowledge obtained from individual city-dwellers through the application of fuzzy relational theory to personal construct theory. Crucial to this research is to implement formally and process interpretatively the psychological cognition of urbanites who interact with their environment in order to offer useful advice on urban problem. What is needed is a techniques to analyze cognitive structures which are embodiments of this perceptive knowledge for human being.

A Design of Spatio-Temporal Data Model for Simple Fuzzy Regions

  • Vu Thi Hong Nhan;Chi, Jeong-Hee;Nam, Kwang-Woo;Ryu, Keun-Ho
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.384-387
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    • 2003
  • Most of the real world phenomena change over time. The ability to represent and to reason geographic data becomes crucial. A large amount of non-standard applications are dealing with data characterized by spatial, temporal and/or uncertainty features. Non-standard data like spatial and temporal data have an inner complex structure requiring sophisticated data representation, and their operations necessitate sophisticated and efficient algorithms. Current GIS technology is inefficient to model and to handle complex geographic phenomena, which involve space, time and uncertainty dimensions. This paper concentrates on developing a fuzzy spatio-temporal data model based on fuzzy set theory and relational data models. Fuzzy spatio-temporal operators are also provided to support dynamic query.

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A Study on Safty Diagnosis and Evaluation of Oil Transformer using Fuzzy Algorithm (퍼지알고리즘을 이용한 유증 변압기의 안전진단 및 평가에 관한 연구.)

  • Kim, Young-Il
    • Proceedings of the KIEE Conference
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    • 2006.07e
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    • pp.67-68
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    • 2006
  • In this paper, we introduced about safety algorithm of transformer for MV/LV distribution customers using by fuzzy theory. Overload of transformer becomes different by surrounding temperature. And parameters about overload of transformer are connection each other. Therefore, we organize safety algorithm consider overload of transformer and surrounding temperature in this research. And we induce the relational expression of each parameters using experiment data of IEEE std C57.91-1995. Deduction of result used fuzzy reasoning. We guess the safety algorithm suggested in this paper shows the new direction that heavy electrical equipments including switchboard are going to develop in the future.

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A Study on Intelligent Image Database based on Fuzzy Set Theory (퍼지이론에 기초한 지적 감성검색시스템에 관한 연구)

  • 김돈한
    • Archives of design research
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    • v.14 no.4
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    • pp.5-14
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    • 2001
  • Among Human Sensibility-oriented products a gap between the images that designers try to express through that product and users emotional evaluation becomes an issue. The data on the correlation between image words used for design evaluation and images used in the design process are especially significant. This study based on these correlations suggests a Fuzzy retrieval system supporting styling design with images and image words. In the system, the relational data are demonstrated by Fuzzy thesaurus as correlation coefficient from the degree of similarity among image words. And the degree of similarity is produced based on image evaluation. Image retrieval is conducted by the algorithm of Fuzzy thesaurus development, 1) among image words, 2) images to image words, 3) image words to images and 4) among images: 4 different modes are provided as retrieval modes. Also transfer between modes is carried by direct operating interface, therefore divergent thinking and convergent thinking is supported well. The system consists of operation for the gap and the measurement unit of emotional evaluation, and visualization units. Under unified interface environments are set in order for consistency of the operation.

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Study of MetaData for Natural Language Query Processing (퍼지질의 처리를 위한 메타데이터에 관한 연구)

  • 신세영;박순철;이상범
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.5
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    • pp.259-265
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    • 2003
  • It leads to develop the query system with artificial intelligent technologies to handle inaccurate query. To develop the query system, metadata is essential to control a uncertain data, providing information about uncertainty of the data, and the classification system of metadata are necessary. This paper shows a classification of metadata based on fuzzy theory and the implementation processing to process the fuzzy query in a relational database system.