• Computational Structural Engineering
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• v.4 no.3
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• pp.107-115
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• 1991

A probabilistic-Fuzzy model for seismic hazard analysis is developed. The proposed model is able to reproduce both the randomness and the imprecision in conjunction with earthquake occurrences. Results-of this research are (a) membership functions of both peak ground accelerations associated with a given probability of exceedance and probabilities of exceedance associated with a given peak ground acceleration, and (b) characteristic values of membership functions at each location of interest. The proposed probabilistic-fuzzy model for assessment of seismic hazard is successfully applied to the Wasatch Front Range in Utah in order to obtain the seismic maps for different annual probabilities of exceedance, different peak ground accelerations, and different time periods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.6
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• pp.54-58
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• 2002

퍼지 균등화는 어의론적으로 의미있고, 실험적으로 의미있는 언어레이블을 붙이도록 하는 조건이다. 지금까지 발표된 퍼지 균등화조건을 갖는 퍼지분할을 생성하는 알고리듬은 주어진 데이터에 대하여, 오직 하나의 퍼지분할만을 생성할 수 있었다. 만일 생성된 퍼지 분할이 더 이상 유용하지 못한 것으로 판명되면, 이 알고리듬은 주어진 데이터에 대한 퍼지 균등화조건을 갖는 또 다른 퍼지분할을 생성할 수 없다. 이는 생성된 퍼지분할을 사용하여 탐색적 발견을 수행하는 데이터마이닝의 경우 더 이상 프로세스가 진행되지 못함을 의미한다. 본 연구에서는 주어진 데이터에 대한 퍼지 균등화조건을 갖는 서로 다른 두 퍼지분할이 존재한다면, 어떠한 관계가 있는지를 증명하고, 이를 위치적 특성으로 서술한다. 또한 이 특성을 이용하여 퍼지 균등화조건을 갖는 퍼지분할을 원하는 만큼 생성할 수 있는 알고리듬을 제시하고, 예를 들어 설명한다.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.6
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• pp.542-546
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• 2007

In the vision of ubiquitous computing environment, smart objects would communicate each other and provide many kinds of information about user and their surroundings in the home. This information enables smart objects to recognize context and to provide active and convenient services to the customers. However in most cases, context-aware services are available only with expert systems. In this paper, we present generalized activity recognition application in the smart home based on a naive Bayesian network(BN) and fuzzy clustering. We quantize continuous sensor data with fuzzy c-means clustering to simplify and reduce BN's conditional probability table size. And we apply mutual information to learn the BN structure efficiently. We show that this system can recognize user activities about 80% accuracy in the web based virtual smart home.

• Journal for History of Mathematics
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• v.14 no.2
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• pp.93-100
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• 2001

The problem of vagueness has been investigated for a long time by philosophers and mathematicians. There are there approaches in mathematics to the problem, which are probability theory, fuzzy logic, and rough set theory. In this paper I introduce these theories and their meanings.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.29-35
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• 2012

This paper introduces an adaptive control method of strong mutation rate and probability for queen-bee genetic algorithms. Although the queen-bee genetic algorithms have shown good performances, it had a critical problem that the strong mutation rate and probability should be selected by a trial and error method empirically. In order to solve this problem, we employed the measure of convergence and used it as a control parameter of those. Experimental results with four function optimization problems showed that our method was similar to or sometimes superior to the best result of empirical selections. This indicates that our method is very useful to practical optimization problems because it does not need time consuming trials.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.31
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• pp.177-186
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• 1994

Most causes of accidents are due to physical unsafety conditions and human unsafety actions. The design of safety work by ergonomics method is one of the methodes which effectively reduce these unsafety conditions and unsafety actions. This paper presents considerations in design of safety work. And when we try to analyze the accident event by means of probability, there exist some problems because of fuzziness in physical unsafety conditions' components and human unsafety actions' components which are the causes of basic event. For this reason, it is impossible for input probability of basic event to define a crisp value. In consideration of the uncertain probability of components, this paper deals with the Fuzzy set theory by membership value and suggests calculation procedure and analysis of disaster event.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.371-374
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• 2009

In this paper, we introduce the concepts of effects and observable as generalizations of event and random variable, respectively. Also, we introduce the concept of $\sigma$-morphism and we investigate some results on $\sigma$-morphism as a probability measure on the set of effects.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.10
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• pp.141-151
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• 1999

The resistance Spot Welding is widely used in the field of assembling the plates. However we don't still have any satisfactory solution, which is non-destructive quality evaluation in real-time or on-line, against it. Moreover, even though the rate of welding under the condition of expulsion has been high until now, quality control of welding against expulsion hasn't still been established. In this paper, it was proposed on the quality assurance technique of resistance spot welding pieces using Neuro-Fuzzy algorithm. Four parameters from electrode separation signal in the case of non-expulsion, and dynamic resistance patterns in the case of expulsion are selected as fuzzy input parameters. The parameters consist of Fuzzy Inference System are determined through Neuro-Learning algorithm. And then, fuzzy Inference System is constructed. It was confirmed that the fuzzy inference values of strength have within ${\pm}$4% error specimen in comparison with real strength for the total strength range, and the specimen percent having within ${\pm}$1% error was 88.8%. According to KS(Korean Industrial Standard), tensile-shear strength limit for electric coated of zinc is 400kgf/mm2. Judging to the quality of welding is good or bad, according to this criterion and the results of inference, the probability of misjudgement that good quality is valuated into poor one was 0.43%, on contrary it was 2.59%. Finally, the proposed Neuro-Fuzzy Inference System can infer the tensile-shear strength of resistance spot welding pieces with high performance for all cases-non-expulsion and expulsion. And On-Line Welding Quality Inspection System will be realized sooner or later.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.421-437
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• 2015

This paper aims to present a supervised classification algorithm based on data fusion for the segmentation of the textured images. The feature extraction method we used is based on discrete wavelet transform (DWT). In the segmentation stage, the estimated feature vector of each pixel is sent to the support vector machine (SVM) classifier for initial labeling. To obtain a more accurate segmentation result, two strategies based on information fusion were used. We first integrated decision-level fusion strategies by combining decisions made by the SVM classifier within a sliding window. In the second strategy, the fuzzy set theory and rules based on probability theory were used to combine the scores obtained by SVM over a sliding window. Finally, the performance of the proposed segmentation algorithm was demonstrated on a variety of synthetic and real images and showed that the proposed data fusion method improved the classification accuracy compared to applying a SVM classifier. The results revealed that the overall accuracies of SVM classification of textured images is 88%, while our fusion methodology obtained an accuracy of up to 96%, depending on the size of the data base.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.