• Journal of the Korean Institute of Intelligent Systems
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• v.4 no.2
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• pp.24-34
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• 1994

Scientific involvement in complex decision-making system, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced and their weighted value structure is ignorant, the systems are become more complex. This paper presents a fuzzy dependenced relation model and fuzzy measure model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation and fuzzy measure in fuzzy systems theory. For the application of the model, a numdrical example is quoted.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.1049-1056
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• 2008

Intuitionistic Fuzzifications of strong hyper K-ideals and hyper K-subalgebras in hyper K-algebras are discussed, and related properties are investigated. Relations between intuitionistic fuzzy hyper K-subalgebras, intuitionistic fuzzy weak hyper K-ideals and intuitionistic fuzzy strong hyper K-ideals are provided.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.742-748
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• 1994

Scientific involvement in complex decision-making systems, characterized by multicriteria phenomena and fuzziness inherent in the structure of information, requires suitable methods. Especially, when powerful dependent criteria are introduced, the systems are become more complex. This paper presents a fuzzy dependence relation model for this kind of multicriteria decision-making. The model we propose is based on fuzzy relation in fuzzy system theory. For the application of the model a numerical example is quoted.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.1
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• pp.41-52
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• 1994

Imprecision of evaluation or lack of prior information about preference can be an obstacle for decision maker in representing his strict preference. Therefore, fuzziness of preference can take place, and in addition, intransitivity or incomparability of preference becomes the critical difficulty in making complete preorder of alternatives. In order to get better solution and to improve practical usufulness, MCDM should be established as a pseudo-criterion model that include fuzzy preference. In this paper, we suggest a pseudo-criterion model that can make complete preorder of alternatives by metric distance measure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.129-132
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• 1996

In this paper, we suggest a framework to represent the fuzziness in knowledge base as a perspective of the object-oriented paradigm. We divide the knowledge base in two parts. One is the object-base that stores the fuzzy propositions and the explanatory databases. The other is the rule-base that manages the rules between the fuzzy propositions. As the first step, we have to develop a new fuzzy object model that gives an easy way to represent the fuzzy propositions, that is, the fuzzy knowledge in the real world.

• Journal of the military operations research society of Korea
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• v.18 no.2
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• pp.56-65
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• 1992

In the existing deterministic network, the capacity of each arc has been assumed to have a determined property. In reality it may have a property which cannot be determined, and even if it is determined, it contains many errors. Fuzzy theory is efficient in dealing with these kinds of properties. The object of this study is to show that the capacity of each arc and the goal quantity have fuzziness and to develop a new method of determining the fuzzy maximal flow quantity.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.749-753
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• 2003

In this paper we introduce the concepts on retrievability, separability and connectedness of fuzzy submachines, which generalize those of crisp submachines. And also we generalize crisp primary submachines to those with fuzziness, from which we obtain the decomposition theorem of fuzzy submachines.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.445-449
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• 2005

Yen et al. [Fuzzy Sets and Systems 106 (1999) 167-177] calculated the fuzzy membership function for the output to find the non-symmetric triangular fuzzy number coefficients of a linear regression model for all given input-output data sets. In this note, we show that the result they obtained in their paper is invalid.

• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.167-178
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• 2003

In mobile computing environments, queries based on the location of mobile clients (MCs) may cause different results. We say that the data of these results are location dependent data (LDD). Location-dependent queries to LDD need to be processed in conjunction with the geographical distance. The efficiency of query processing may also be increased by LDD relationship, etc. But there is the problem of fuzziness about how the distance used in location-dependent queries is evaluated and the data regions are organized. In this paper, we quantify the fuzziness of a location-dependent fuery on LDD. And we propose data regions for LDD, called LDD regions, by relationship of accessed data and the degree of distance between data objects and MCs' locations. In simulation studies we show that the number of database access for location-dependent queries, which have several settings on MCs' favor and two granularity of regions, can be smaller in proposed LDD regions than that in geographical regions.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.315-323
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• 2001

The concept of vertical partitioning has been discussed so far in an objective of improving the performance of query execution and system throughput. It can be applied to the areas where the match between data and queries affects performance, which includes partitioning of individual files in centralized environments, data distribution in distributed databases, dividing data among different levels of memory hierarchies, and so on. In general, a vertical partitioning algorithm should support n-ary partitioning as well as a globally optimal solution for the generation of all meaningful fragments. Most previous methods, however, have some limitations to support both of them efficiently. Because the vertical partitioning problem basically includes the fuzziness property, the proper management is required for the fuzziness problem. In this paper we propose an efficient vertical $\alpha$-partitioning algorithm which is based on the fuzzy theory. The method can not only generate all meaningful fragments but also support n-ary partitioning without any complex mathematical computations.