• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1085-1087
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• 1999

In this paper, we propose the method for assessing the effect of voltage sag in power distribution system using fuzzy risk assessment model. The proposed method is based on SCBEMA curve that expresses the representative susceptibility curve by voltage sag for each customer type. These corves are made using the CBEMA curves obtained from the experiment for the customers'sensitive equipment. In order to transform SCBEMA curves to the probability damage by voltage sag, the fuzzy risk assessment model is used in this paper. Case studies were performed to analyze the effect of voltage sag by varying parameters. The Monte Carlo simulation method and the historical reliability data in KEPCO are used for case studies.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.519-524
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• 2001

Recently, our construction market recognizes the necessity of risk management, however the application of practical system is still limited on the construction site because the methodology for analyzing and quantifying construction risk and for building actual risk factors is not easy. This study suggests a risk management method by fuzzy theory, which is using subjective knowledge of an expert and linguistic value, to analyze and Quantify risk. The result of study is expected to improve the accuracy of risk analysis because three factors, such as probability, impact and frequency, for estimating membership function are introduced to quantify each risk factor.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.891-893
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• 1997

In this paper an intelligent power transformer protective relaying algorithm based on Fuzzy Decision-Making is presented. The introduced protection algorithm contains several internal fuzzy rule-bases including bpa(Basic Probability Assignment: m) which are subject to off-line pre-installation by the analysis of the transformer transient characteristics for detecting the internal fault. Dempster-Shafer's rule of combination is used for the inference method with rules to decide the situation of a transformer, The proposed algorithm immunes to the saturation of transformer, inrush conditions, over excitation, and external fault. The included results of testing show practically sufficient sensitivity and selectivity of the proposed algorithm.

• Ocean Systems Engineering
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• v.9 no.3
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• pp.261-285
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• 2019

Nowadays in offshore industry there are emerging hazards with vague property such as act of terrorism, act of war, unforeseen natural disasters such as tsunami, etc. Therefore industry professionals such as offshore energy insurers, safety engineers and risk managers in order to determine the failure rates and frequencies for the potential hazards where there is no data available, they need to use an appropriate method to overcome this difficulty. Furthermore in conventional risk based analysis models such as when using a fault tree analysis, hazards with vague properties are normally waived and ignored. In other word in previous situations only a traditional probability based fault tree analysis could be implemented. To overcome this shortcoming fuzzy set theory is applied to fault tree analysis to combine the known and unknown data in which the pre-combined result will be determined under a fuzzy environment. This has been fulfilled by integration of a generic bow-tie based risk analysis model into the risk assessment phase of the Risk Management (RM) cycles as a backbone of the phase. For this reason Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) are used to analyse one of the significant risk factors associated in offshore terminals. This process will eventually help the insurers and risk managers in marine and offshore industries to investigate the potential hazards more in detail if there is vagueness. For this purpose a case study of offshore terminal while coinciding with the nature of the Caspian Sea was decided to be examined.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.254-258
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• 2004

In this paper, we propose a robust speech recognition system under noisy environments. Since the presence of noise severely degrades the performance of speech recognition system, it is important to design the robust speech recognition method against noise. The proposed method adopts a new distance measure technique based on stochastic probability instead of conventional method using minimum error. For evaluating the performance of the proposed method, we compared it with conventional distance measure for the 10-isolated Korean digits with car noise. Here, the proposed method showed better recognition rate than conventional distance measure for the various car noisy environments.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.90-97
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• 2003

This paper proposes a speech recognition based on HMM(Hidden Markov Model) using FSVQ(First Section Vector Quantization) and fuzzy concept. In the proposed paper, we generate codebook of First Section, and then obtain multi-observation sequences by order of large propabilistic values based on fuzzy rule from the codebook of the first section. Thereafter, this observation sequences of first section from codebooks is trained and in case of recognition, a word that has the most highest probability of first section is selected as a recognized word by same concept. Train station names are selected as the target recognition vocabulary and LPC cepstrum coefficients are used as the feature parameters. Besides the speech recognition experiments of proposed method, we experiment the other methods under same conditions and data. Through the experiment results, it is proved that the proposed method based on HMM using FSVQ and fuzzy concept is superior to tile others in recognition rate.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.166-181
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• 1996

Aircraft survivability is determined by the susceptibility and the vulnerability. The aircraft susceptibility and vulnerability depend upon the hardware and software factors. Each of the hardware and software factors consisted of the qualitative and quantitative attributes varies according to the time of the mission. In order to establish the mathermatical model to analyze and evaluate the aircraft survivability, qualitative factors have to be transformed into quantitative factors. Even if many researches in the area of dynamic concept analysis and conversion of qualitative factors into the quantitative factors has been insufficient. This research enhances these insufficient area by developing a reliable aircarft survivability analysis method. The major areas of this research are as follows. First, a method for the conversion of the qualitative factors into the quantitative factors is developed by combining the Fuzzy Set Theory concept and the Delphi Technique. Second, by using the stochastic network diagram for the dynamic survivability analysis, the aircraft survivability and the probability of kill are calculated from the state probability for the situation during mission. The advantage of the analysis technique developed in this research includes ease of use and flexibility. In other words, in any given aircraft's mission execution under any variable probability density function, the developed computer program is able to analyze and evaluate the aircraft survivability.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.146-151
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• 2010

This paper proposes a rank-based control method of mutation probability for improving the performances of genetic algorithms (GAs). In order to improve the performances of GAs, GAs should not fall into premature convergence phenomena and should also be able to easily get out of the phenomena when GAs fall into the phenomena without destroying good individuals. For this, it is important to keep diversity of individuals and to keep good individuals. If a method for keeping diversity, however, is not elaborately devised, then good individuals are also destroyed. We should devise a method that keeps diversity of individuals and also keeps good individuals at the same time. To achieve these two objectives, we introduce a rank-based control method of mutation probability in this paper. We set high mutation probabilities to lowly ranked individuals not to fall into premature convergence phenomena by keeping diversity and low mutation probabilities to highly ranked individuals not to destroy good individuals. We experimented our method with typical four function optimization problems in order to measure the performances of our method. It was found from extensive experiments that the proposed rank-based control method could accelerate the GAs considerably.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.649-664
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• 2017

Purpose: This paper introduces the technology of prognostics for Industry 4.0 and presents its application procedure for fitness-for-service assessment of natural gas pipelines according to ISO 13374 framework. Methods: Combining data-driven approach with pipe failure models, we present a hybrid scheme for the gas pipeline prognostics. The probability of pipe failure is obtained by using the PCORRC burst pressure model and First Order Second Moment (FOSM) method. A fuzzy inference system is also employed to accommodate uncertainty due to corrosion growth and defect occurrence. Results: With a modified field dataset, the probability of failure on the pipeline is calculated. Then, its residual useful life (RUL) is predicted according to ISO 16708 standard. As a result, the fitness-for-service of the test pipeline is well-confirmed. Conclusion: The framework described in ISO 13374 is applicable to the RUL prediction and the fitness-for-service assessment for gas pipelines. Therefore, the technology of prognostics is helpful for safe and efficient management of gas pipelines in Industry 4.0.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.111-126
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• 1999

The article is devoted to mathematical modeling of prob-lems of stochastic optimization of the plastic metal working. Classifi-cation and mathematical statements of such problems are proposed. Several calculation techniques of the single goal function are pre-sented. The probability theory and the Fuzzy numbers were applied for solution of the problems of stochastic optimization.