• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.2
• /
• pp.222-230
• /
• 2003

Once the medical knowledge-based system has been developed, it is essential to investigate the knowledge sources of the system because knowledge sources can affect the performance of the system in great deal. This paper presents the method and the results of the reliability test done on the medical knowledge-based system CLINAID. A knowledge source tested is Cardiovascular body system data used in CLINAID. The reliability test will be done by investigating structural relationships revealed by fuzzy relational method between the components of the knowledge sources of individual body systems using syndromes as its main component. These partitions are going to be compared with the syndromes elicited from the medical experts. This paper also reports the outcome of the computations using 7 implication operators performed on Cardiovascular body system data.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.579-583
• /
• 1991

A fuzzy logic controller with rule modification capability is proposed to overcome the difficulty of obtaining control rules from the human operators. This new SOC algorithm modifies control rules by a fuzzy inference machine utilizing data base. Computer simulation results show good performances on both a linear system and a nonlinear system.

• Korean Journal of Mathematics
• /
• v.25 no.1
• /
• pp.71-85
• /
• 2017

This paper introduces a novel extension of soft rough fuzzy set so-called modified soft rough fuzzy set model in which new lower and upper approximation operators are presented together their related properties that are also investigated. Eventually it is shown that these new models of approximations are finer than previous ones developed by using soft rough fuzzy sets.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.4
• /
• pp.404-410
• /
• 1999

We will prove the existence of initial fuzzy closure structures. From this fact we can define subspaces and products of fuzzy closure spaces. Furthermore the family $\Delta$(X) of all fuzzy closure operators on X is a complete lattice. In particular an initial structure of fuzzy topological spaces can be obtained by the initial structure of fuzzy closure spaces induced by those. We suggest some examples of it.

• Korean Journal of Remote Sensing
• /
• v.21 no.2
• /
• pp.145-162
• /
• 2005

To improve the accuracy of land-cover discrimination in SAB data classification, this paper presents a methodology that includes feature extraction and fusion steps with multi-temporal SAR data. Three features including average backscattering coefficient, temporal variability and coherence are extracted from multi-temporal SAR data by considering the temporal behaviors of backscattering characteristics of SAR sensors. Dempster-Shafer theory of evidence(D-S theory) and fuzzy logic are applied to effectively integrate those features. Especially, a feature-driven heuristic approach to mass function assignment in D-S theory is applied and various fuzzy combination operators are tested in fuzzy logic fusion. As experimental results on a multi-temporal Radarsat-1 data set, the features considered in this paper could provide complementary information and thus effectively discriminated water, paddy and urban areas. However, it was difficult to discriminate forest and dry fields. From an information fusion methodological point of view, the D-S theory and fuzzy combination operators except the fuzzy Max and Algebraic Sum operators showed similar land-cover accuracy statistics.

• Communications of the Korean Mathematical Society
• /
• v.32 no.2
• /
• pp.333-352
• /
• 2017

In this research work, by using the random resolvent operator techniques associated with random ($A_t$, ${\eta}_t$, $m_t$)-monotone operators, is to established an existence and convergence theorems for a class of fuzzy system of random nonlinear equations with fuzzy mappings in Hilbert spaces. Our results improve and generalized the corresponding results of the recent works.

• Kyungpook Mathematical Journal
• /
• v.50 no.4
• /
• pp.465-472
• /
• 2010

In this paper, we consider two extreme sets of zero-term rank sum of fuzzy matrix pairs: $$\cal{z}_1(\cal{F})=\{(X,Y){\in}\cal{M}_{m,n}(\cal{F})^2{\mid}z(X+Y)=min\{z(X),z(Y)\}\};$$ $$\cal{z}_2(\cal{F})=\{(X,Y){\in}\cal{M}_{m,n}(\cal{F})^2{\mid}z(X+Y)=0\}$$. We characterize the linear operators that preserve these two extreme sets of zero-term rank sum of fuzzy matrix pairs.

• Honam Mathematical Journal
• /
• v.33 no.3
• /
• pp.301-310
• /
• 2011

In this paper, we construct the sets of fuzzy matrix pairs. These sets are naturally occurred at the extreme cases for the zero-term rank inequalities derived from the multiplication of fuzzy matrix pairs. We characterize the linear operators that preserve these extreme sets of fuzzy matrix pairs.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.28B no.11
• /
• pp.941-954
• /
• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating point. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1998.06a
• /
• pp.745-749
• /
• 1998

Mathematical morphology (MM) has been introduced as a powerful tool for studying the geometrical properties of images, MM is a good approach to digital image processing , which is based on the shape feature. The MM operators such as dilation, erosion, closing and opening have been applied successfully to image noise reduction. The MM filters can easily filter the noise when the noise factors are known. However it is very difficult to reduce the noise when images are ambiguous, because the boundary between the noise and object is vague. In this paper, we propose a new method to reduce noise from ambiguous images by using Fuzzy Mathematical Morphology (FMM) operators. Performance evaluation via simulations show that the FMM filters efficiently reduce the image noise. Furthermore, the FMM filters show a good performance compared with the conventional filters.