• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.333-336
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• 2002

In many cases, fuzzy modeling has a defect that the design procedure cannot be theoretically justified. To overcome this difficulty, we suggest a new design method for fuzzy model by combining genetic algorithm(GA) and mush set theory. GA, which has the advantages is optimization, and rule base. However, it is some what time consuming, so are introduce rough set theory to the rule reduction procedure. As a result, the decrease of learning time and the considerable rate of rule reduction is achieved without loss of useful information. The preposed algorithm is composed of three stages; First stage is quasi-optimization of fuzzy model using GA(coarse tuning). Next the obtained rule base is reduced by rough set concept(rule reduction). Finally we perform re-optimization of the membership functions by GA(fine tuning). To check the effectiveness of the suggested algorithm, examples for time series prediction are examined.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.59-66
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• 2004

We define a SG(String Graph) and an ASG(Alive String Graph) to the purpose to do static analysis. For a life and death judgment, we apply the rule to the situation which the stone is included and not included. We define the rules that are SR(String Reduction), ER(Empty Reduction), ET(Edge Transform), and CG(Circular Graph), when the stone is not included. We define the rules that are DESR(Dead Enemy Strings Reduction) and SCSR(Same Color String Reduction), when the stone is included. We evaluate a SG that it is an ASG or not by using rules. And we use APC(Articulation Point Check) nile according to number of articulation points lot a life and death judgment. The performance of our method has been tested on the problem set IGS_31_counted form the Computer Go Test Collection. The test set contains 11,191 Points and 1,123 Strings. We obtain 92.5% accuracy of Points and 95.7% accuracy of Strings.

• Coupled systems mechanics
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• v.9 no.3
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• pp.281-287
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• 2020

Nanotechnology is an upcoming technology that can provide solution for combating pollution by controlling shape and size of materials at the nanoscale. This review provides comprehensive information regarding the role of nanotechnology in pollution control at concrete structures. Titanium dioxide (TiO2) nanoparticles are a good item for concrete structures for diminishing the air polluting affect by gasses of exhaust. In this article, the mixture rule is presented for the effect of nanoparticles in environmental pollution reduction in concrete structures. The compressive strength, elastic modulus and reduction of steel bars in the concrete structures are studied. The Results show that TiO2 nanoparticles have significant effect on the reduction of environmental pollution and increase of stiffness in the concrete structures. In addition, the nanoparticles can reduce the use of steel bars in the concrete structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.78-81
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• 2003

This paper proposes a fuzzy classifier system (FCS) using hyper-cone membership functions (HCMFs) and rule reduction techniques. The FCS can generate excellent rules which have the best number of rules and the best location and shape of membership functions. The HCMF is expressed by a kind of radial basis function, and its fuzzy rule can be flexibly located in input and output spaces. The rule reduction technique adopts a decreasing method by merging the two appropriate rules. We applay the FCS to a tubby rule generation for the inverted pendulum control.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.37-43
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• 2011

In pattern analysis, dimensionality reduction and reasonable identification rule generation are very important parts. This paper performed effectively the dimensionality reduction by grouping the sensors of which the measured patterns are similar each other, where genetic algorithms were used for combination optimization. To identify the gas type, this paper constructed the hierarchically identifiable rule base with two frames by using rough set theory. The first frame is to accept measurement characteristics of each sensor and the other one is to reflect the identification patterns of each group. Thus, the proposed methods was able to accomplish effectively dimensionality reduction as well as accurate gas identification. In simulation, this paper demonstrated the effectiveness of the proposed methods by identifying five types of gases.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.285-290
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• 2009

An association rule mining has been studied to find hidden data pattern in data mining. A realization of fast processing method have became a big issue because it treated a great number of transaction data. The time which is derived by association rule finding method geometrically increase according to a number of item included data. Accordingly, the process to reduce the number of rules is necessarily needed. We propose the T-algorithm that is efficient rule reduction algorithm. The T-algorithm can reduce effectively the number of association rules. Because that the T-algorithm compares transaction data item with binary format. And improves a support and a confidence between items. The performance of the proposed T-algorithm is evaluated from a simulation.

• Cross-Cultural Studies
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• v.30
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• pp.97-124
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• 2013

For a long period, vowel reduction has been accepted as one of the most common pronunciation rules in Russian phonology. However, since the rules have been modified in many ways after the influx of loanwords, [a, e, i, o, u, ${\star}$]-including [e, o]-can now be pronounced in unstressed position, obeying the rule of vowel reduction. Especially in Modern Russian, along with the destruction of the consonant pronunciation norm due to some relatively complex changes it underwent palatalization, consonant pronunciation has been simplified, and as a response to such a phenomenon, the specialization of vowel pronunciation rule is now occurring. In other words, in the interrelation between consonants and vowels, as the pronunciation rules for consonants are simplified and thus the contrast between consonants is weakened, the degree of dependence on pronunciation of segment in the vowel pronunciation rule has been elevated. Therefore, the analysis says that the degree of vowel reduction depends on a vowel's distance from a stressed syllable is not enough; the influence of surrounding phonemes-including consonants-or the formative characteristics of words themselves should also be considered. The introduction of Max-noncorner/UnderLex, a/an Licence constraint that is related to non-declension nouns, and that of IdentC[back] and ShareCV[back], which are faithfulness constraint and share constraint respectively that are related to the nature of consonants stresses that vowel pronunciation rules should not be simply viewed as rules for vowels; The rules should be analyzed with emphasis on their correlation with surrounding phonemes.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.319-326
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• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.

• Journal of Korea Multimedia Society
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• v.13 no.9
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• pp.1329-1336
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• 2010

Cellular Automata is a discrete dynamical system which natural phenomena may be specified completely in terms of local relation, can increase and decrease the difference of luminance locally according to transition rule by keeping the characteristic of target image. In this paper, we propose a noise reduction method by keeping the characteristic using transition rule of Cellular Automata, also we propose methods of effective transition rule, the selection of parameters, the selection of number of neighborhood pixels. For uniform distribution noise, Gaussian noise, impulse noise, we do an experiment on adaptive state using different mathematical operations and compare its results. It was confirmed that the proposed transition rule is based on fast convergence speed and has stabile results.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.109-118
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• 2007

This paper proposed a method that can be simply analyzed instead of the basic general Fuzzy rule that its insufficient characters are cut out. Based on the proposed method. Rough sets are used to eliminate the incomplete attributes included in the rule and also for a classification more precise; the agreement of the membership function's output extracted the maximum attributes. Besides, the proposed method in the simulation shows that in order to verify the validity, compare the max-product result of fuzzy before and after reducing rule hosed on the rice taste data; then, we can see that both the max-product result of fuzzy before and after reducing rule are exactly the same; for a verification more objective, we compared the defuzzificated real number section.