• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.668-671
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• 1997

This paper describes a new process-plan selection method using a modified Fuzzy Quantification Theory(FQT). The problem for process-plan selection can be characterized by multiple attributes and used subjective, uncertain information. Fuzzy Quantification Theory is used for handling such informations because it is a useful tool when human judgment or evaluation is quantified via linguistic variables and the proposed method is concerned with the selection of a process plan by derivation of the values of categories for each attribute. In this paper, a modified Fuzzy Quantification Theory(FQT) is described and the procedure of this approach is explained and examples are illustrated.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.490-496
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• 1997

This paper describes a new process-plan selection method using a modified Fuzzy Quantification Theory(FQT). The problem of process-plan selection can be characterized by multiple attributes and used subjective, uncertain information. Fuzzy Quantification Theory is used for handling such information because it is a useful tool when human judgment or evaluation is quantified via linguistic variables, and the proposed method is concerned with the selection of a process plan by derivation of the values of categories for each attribute. In this paper, a modified Fuzzy Quantification Theory(FQT) is described and the procedure of this approach is explained and examples illustrated.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.417-424
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• 1995

This paper describes MFT(Mean Field Theory) neural network with continuous with continuous variables is applied to quantification analysis problem. A quantification analysis problem, one of the important problems in statistics, is NP complete and arises in the optimal location of objects in the design space according to the given similarities only. This paper presents a MFT neural network with continuous variables for the quantification problem. Starting with reformulation of the quantification problem to the penalty problem, this paper propose a "one-variable stochastic simulated annealing(one-variable SSA)" based on the mean field approximation. This makes it possible to evaluate of the spin average faster than real value calculating in the MFT neural network with continuous variables. Consequently, some experimental results show the feasibility of this approach to overcome the difficulties to evaluate the spin average value expressed by the integral in such models.ch models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.259-266
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• 2017

In modern society, IT technology based systems are introduced and operated in various fields such as home, industry, and finance. To ensure the safety of society, IT systems introduced throughout society should be protected from cyber attacks. Understanding and checking the current security status of the system is one of the important tasks to response effectively against cyber attacks. In this paper, we analyze limitations of Game Theory and Attack Tree methodologies used to inspect for security vulnerabilities. Based on this, we propose a security vulnerability quantification method that complements the limitations of both methodologies. This provides a more objective and systematic way to inspect for security weaknesses.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.1
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• pp.59-67
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• 2016

Owing to time and cost constraints, new methods that would make it possible to evaluate the safety of the water supply pipeline in a less time- and cost-consuming manner are urgently needed. In response to this exigency, the present study developed a new statistical model to assess the safety of the water supply pipeline using the quantification theory type II. In this research, the safety of the water supply pipeline was defined as 'a possibility of the pipeline failure'. Quantification analysis was conducted on the qualitative data, such as pipe material, coating, and buried condition. The results of analyses demonstrate that the hit ratio of the quantification function amounted to 77.8% of hit ratio, which was a fair value. In addition, all variables that were included in the quantification function were logically valid and demonstrated statistically significant. According to the results derived from the application of the safety evaluation model, the coefficient of determination ($R^2$) between K-region's water supply pipeline safety and the safety inspection amounted to 0.80. Therefore, these findings provide meaningful insight for the measured values in real applications of the model. The results of the present study can also be meaningfully used in further research on safety evaluation of pipelines, establishing of renewal prioritization, as well as asset management planning of the water supply infrastructure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.206-211
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• 2006

The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.589-601
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• 1996

Geometric approach to extend the classical two-set theory of canonical correlation analysis to three or more sets is considered. It provides statistical graphs to represent the data in a low dimensional space. Procedures are developed for computing the canonical variables and the corresponding properties are investigated. The solution is equivalent to that of the usual problem in the case of two sets. Goodness-of-fit of the proposed plots is studied and a numerical example is included.

• Journal of Forest and Environmental Science
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• v.18 no.1
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• pp.7-14
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• 2001

On the basis of data obtained from forest road collapsed due to a heavy rainfall, this study carried out to evaluate the cutting slope failure factors of forest road by using Quantification theory(II). The results were summarized as follows. The factors on cutting slope failure was ranked in the order of cutting slope length, soil type, aspect, cutting slope gradients and slope gradients. And the slope failure was mainly occurred under such conditions as cutting slope length longer than 8m, soil type with soil, aspect of N, cutting slope gradients steeper than 600 and slope gradients greater than $35{\sim}40^{\circ}$.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.101-108
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• 2000

In this study, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river, This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.428-434
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• 2022

This study was conducted to derive the site index of forest productivity of Robinia pseudoacacia (honey plant) to characterize suitable planting sites and to investigate the effect of the site environmental factors on the site index using the quantification theory I method. The data used in the analysis were growth factors (stand age, dominant height, etc.) of the 6th national forest resources survey and various site environmental factors of a forest soil map (1:5,000). The average site index value of the R. pseudoacacia stand in Korea was 14 (range, 8 to 18). The environmental factors affecting the site index were parent rock, climatic zone, soil texture, local topography, and altitude. The accuracy of the estimation model using quantification theory I was only 33%. However, the correlation between the site index and the site environmental factors was statistically significant at the 1% level. Results of quantification analysis between site index and site environmental factors revealed that metamorphic and igneous rocks received high grades as parent rocks, climate zones received higher grades than central temperate zone, clay loam and silt loam received high grades in soil texture, and hillside received a high grade in local topography. Analysis of the partial correlation between site topographical factors and forest productivity (site index) found that soil class and altitude were partially correlated to x by 0.4129 and 0.4023, respectively, indicating that these factors are the most influential variables.