• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.417-423
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• 2005

A fuzzy approach using an EM algorithm for image classification is presented. In this study, a double compound stochastic image process is assumed to combine a discrete-valued field for region-class processes and a continuous random field for observed intensity processes. The Markov random field is employed to characterize the geophysical connectedness of a digital image structure. The fuzzy classification is an EM iterative approach based on mixture probability distribution. Under the assumption of the double compound process, given an initial class map, this approach iteratively computes the fuzzy membership vectors in the E-step and the estimates of class-related parameters in the M-step. In the experiments with remotely sensed data, the MRF-based method yielded a spatially smooth class-map with more distinctive configuration of the classes than the non-MRF approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.116-120
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• 2008

Clustering is a method for unsupervised learning. General clustering tools have been depended on statistical methods and machine learning algorithms. One of the popular clustering algorithms based on machine learning is the self organizing map(SOM). SOM is a neural networks model for clustering. SOM and extended SOM have been used in diverse classification and clustering fields such as data mining. But, SOM has had a problem determining optimal number of clusters. In this paper, we propose an improvement of SOM using gap statistic and probability distribution. The gap statistic was introduced to estimate the number of clusters in a dataset. We use gap statistic for settling the problem of SOM. Also, in our research, weights of feature nodes are updated by probability distribution. After complete updating according to prior and posterior distributions, the weights of SOM have probability distributions for optima clustering. To verify improved performance of our work, we make experiments compared with other learning algorithms using simulation data sets.

• Journal of the Korean Society of Safety
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• v.12 no.3
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• pp.155-160
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• 1997

The conventional fault tree and reliability analysis gives in many cases insufficient information concerning the relative frequencies of hazard events. This stems from that the basic events are not stationary and ergodic, and therefore the tolerances of the induced and top events cannot be calculated reliably based on the classical probability theory. To overcome this difficulty, the paper considers the relative frequencies of the basic events as fuzzy numbers and uses instead of probability, possible considerations for evaluating the mean values and tolerances of the top events. The possibility distribution of the basic events can be approximated based on heuristic considerations. This paper shows the use of these operators for constructing fault trees. The use of the method for numerical calculation is demonstrated on a field safety problem.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.1
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• pp.76-84
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• 2000

As first step of any acoustic defence system, a attacking target warning system needs to be extremely reliable. This means the system must ensure a high probability of target classification together with a very low false alarm rate. In this paper, a algorithms for underwater target automatic classification is available for use in the passive sonar will be presented. In first, we will describe the precise automatic extraction of frequency lines for the detection of acoustic signatures. Also, a neural network and fuzzy based algorithms for target classification will be described. Thus the performances of these algorithms are very good with a high probability of classification.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.318-328
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• 2020

Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade.

• Journal of the Korea Safety Management & Science
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• v.4 no.4
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• pp.97-108
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• 2002

This study deals with the application of knowledge-based engineering and a methodology for the assessment & measurement of reliability, availability, maintainability, and safety of industrial systems using fault-tree representation. A fuzzy methodology for fault-tree evaluation seems to be an alternative solution to overcome the drawbacks of the conventional approach. To improve the quality of results, the membership functions must be approximated based on heuristic considerations. Conventionally, it is not always easy to obtain a system reliability for components with different individual failure probability density functions(p.d.f.), We utilize fuzzy set theory to solve the adequacy of the conventional probability in accounting and processing of built-in uncertainties in the probabilistic data. The purpose of this study is to propose the framework of knowledge-based engineering through integrating the various sources of knowledge involved in a FTA.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.698-703
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• 1994

In the actual sound environment, the random signal often shows a complex fluctuation pattern apart from a standard Gaussian distribution. In this study, an evaluation method for the sound environmnetal system is proposed in the generalized form applicable to the actual stochastic phenomena, by introducing two type information processing methods based on the regression model of expansion series type and the Fuzzy probability. The effectiveness of the proposed method are confirmed experimentally too by applying it to the observed data in the actual noise environment.

• The Journal of Asian Finance, Economics and Business
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• v.4 no.1
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• pp.39-49
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• 2017

This study develops an early warning system (EWS) to prevent the banking crisis. The proposed system incorporates both the perspective of crises and fundamental characteristics of the banking system in each economy. A fuzzy logic method with data from 1990-2009 is employed to construct the EWS of banking crisis based on 21 pre-determined variables from the aspect of total economy, financial and banking sectors. Our results show: Firstly, South Korea recorded higher probability to have a banking crisis in 1997 as there was large foreign debt in dollars. Secondly, China, Australia and New Zealand banking systems appear to be vulnerable to the crisis in 2007. The surge of China export, FDIs and booming stock market were signs of a heated economy. Australia with high commodity prices was also vulnerable to crisis. Thirdly, Australia, China, Japan and New Zealand banking systems appear to be exposed to the higher chance of a crisis in 2010. Japan with deflation coupled with expensive yen did not augur well for its export. Overall, the findings show that in Asian Financial Crisis 1997/98 and Global Financial Crisis 2008/09, many economies are exposed to a higher probability of having the crisis and this shows an urgent need of having surveillance in these economies.

• Journal of the Korean Society of Safety
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• v.21 no.2 s.74
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• pp.22-28
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• 2006

This paper presents assessment of possibility on the human risk for the electromagnetic field of unbalanced two coupled three-phase transmission line using fuzzy theory. Three phase load flow program was developed which employed a Newton-Raphson method as a tool to analyze system unbalanced. This research presents a method of handling two coupled three phase transmission system unbalance analysis and unbalanced power demand as a function of voltages. As the results of case study, in case of 345[kV] T/L, the electric field intensity was 10.9540[kV/m], magnetic field intensity was 0.2567[G] in severest case. The results showed that the membership of a proposition fuzzy '10.9540 [kV/m] is hazardous' is 0.6349. As the analytic results using the fuzzy qualifier term, the membership in case of very false is 0.1379 and fairly false is 0.6124, respectively. In assessment of fuzzy measure possibility for the electromagnetic field, this paper used probability of fuzzy arid measure of fuzziness technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.43-51
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• 1996

Fuzzy rules in fuzzy logic control play a major role in deciding the control dynamics of a fuzzy logic controller. Thus, control performance is mainly determined by the quality of fuzzy rules. This paper introduces an optimization method for fuzzy rules using GAS with adaptive probabilies of crossover and mutation. Also we design two fitness measures to satisfy control objectives by partitioning the response of a plant into two parts. An initial population is generated by an automatic fuzzy rule generation method instead of random selection for fast a.pproaching to the final solution. We employed a nonlinear plant to simulate our method. It is shown through simulation that our method is reasonable and can be useful for optimizing fuzzy rules.