• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.532-539
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• 1996

Existing assessment methodologies present a considerable problem because of fuzzy situation of deterioration mechanism of concrete bridges; namely, qualitative, subjective or inconsistent. This paper discusses current assessment methods in aspect of uncertainty. The expert system, COBDA, is developed for consistent and fast assessment of deteriorantion of concrete bridges. Briefly introduced in this paper are the structure of expert system and several methodologies for decision making of deterioration situation and providing repair option. COBDA is configured by PROLOG for logic approach and expert system shell based on Bayesian subjective probability. The methodologies are illustrated and discussed by comparison of condition assessment results in a case study.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.17-23
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• 2016

In the future network such as Internet of Things (IoT), the number of computing devices are expected to grow exponentially, and each of the things communicates with the others and acquires information by itself. Due to the growing interest in IoT applications, the broadcasting in Opportunistic ad-hoc networks such as Machine-to-Machine (M2M) is very important transmission strategy which allows fast data dissemination. In distributed networks for IoT, the energy efficiency of the nodes is a key factor in the network performance. In this paper, we propose a fuzzy logic based probabilistic multi-hop broadcast (FPMCAST) algorithm which statistically disseminates data accordingly to the remaining energy rate, the replication density rate of sending node, and the distance rate between sending and receiving nodes. In proposed FPMCAST, the inference engine is based the fuzzy rule base which is consists of 27 if-then rules. It maps input and output parameters to membership functions of input and output. The output of fuzzy system defines the fuzzy sets for rebroadcasting probability, and defuzzification is used to extract a numeric result from the fuzzy set. Here Center of Gravity (COG) method is used to defuzzify the fuzzy set. Then, the performance of FPMCAST is evaluated through a simulation study. From the simulation, we demonstrate that the proposed FPMCAST algorithm significantly outperforms flooding and gossiping algorithms. Specially, the FPMCAST algorithm has longer network lifetime because the residual energy of each node consumes evenly.

• Structural Engineering and Mechanics
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• v.62 no.4
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• pp.507-517
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• 2017

Due to the discontinuous nature of uncertainty quantification in conventional evidence theory(ET), the computational cost of reliability analysis based on ET model is very high. A novel ET model based on fuzzy distribution and the corresponding combination rule to synthesize the judgments of experts are put forward in this paper. The intersection and union of membership functions are defined as belief and plausible membership function respectively, and the Murfhy's average combination rule is adopted to combine the basic probability assignment for focal elements. Then the combined membership functions are transformed to the equivalent probability density function by a normalizing factor. Finally, a reliability analysis procedure for structures with the mixture of epistemic and aleatory uncertainties is presented, in which the equivalent normalization method is adopted to solve the upper and lower bound of reliability. The effectiveness of the procedure is demonstrated by a numerical example and an engineering example. The results also show that the reliability interval calculated by the suggested method is almost identical to that solved by conventional method. Moreover, the results indicate that the computational cost of the suggested procedure is much less than that of conventional method. The suggested ET model provides a new way to flexibly represent epistemic uncertainty, and provides an efficiency method to estimate the reliability of structures with the mixture of epistemic and aleatory uncertainties.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.303-309
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• 2004

In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.5
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• pp.576-584
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• 2014

In this paper, a study on the optimization of fuzzy classifier using radar cross section(RCS) values is presented to classify shell-shaped targets. Method of moments(MOM) is exploited to construct RCS database of generic shell-shaped targets in uniform angular intervals. Relative orientations are estimated from various flight scenarios of shell-shaped targets, and associated RCS values are interpolated from the generated RCS database with uniform angular intervals. Initial membership functions are determined using the interpolated RCS values, and particle swarm optimization(PSO) is utilized to optimize the membership functions of the fuzzy classifier in terms of probability of correct classification.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.519-527
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• 2020

Dynamic analysis of a vehicle-track coupling system is important to structural design, damage detection and condition assessment of the structural system. Deterministic analysis of the vehicle-track coupling system has been extensively studied in the past, however, the structural parameters of the coupling system have uncertainties in engineering practices. It is essential to treat the parameters of the vehicle-track coupling system with consideration of uncertainties. In this paper, a method for predicting the bounds of the vehicle-track coupling system responses with uncertain parameters is presented. The uncertain system parameters are modeled as fuzzy variables instead of conventional random variables with known probability distributions. Then, the dynamic response functions of the coupling system are transformed into a component function based on the high dimensional representation approximation. The Lagrange interpolation method is used to approximate the component function. Finally, the bounds of the system's dynamic responses can be predicted by using Monte Carlo method for the interpolation polynomials of the Lagrange interpolation function. A numerical example is introduced to illustrate the ability of the proposed method to predict the bounds of the system's dynamic responses, and the results are compared with the direct Monte Carlo method. The results show that the proposed method is effective and efficient to predict the bounds of the system's dynamic responses with fuzzy variables.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.2
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• pp.75-82
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• 2010

The economical efficiency and easy ship building have enabled to spread FRP ships in the shipbuilding field. As waste FRP ships have been thrown away at a river or within a harbour, this matter has become issues. For the improvement of this matter, the melting technique and system of waste FRP ships was developed. But, Decision making was required for a location plan of the melting system of waste FRP ships. It's recognized that the location decision of this system is difficult due to the dependence on technical, economical, environmental factors. In this paper, we survey the primary factors of location-economic, life-environment, infrastructure and make up a question for the experts. We also calculate the important weight and related weight using Fuzzy AHP, Limiting probability method and discuss on the calculation results on the proposed sites.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.4
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• pp.964-969
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• 2008

This paper proposes a HMM-based recognition method using DMSVQ(Dynamic Multi-Section Vector Quantization) codebook by DMS(Dynamic Multi-Section) model and fuzzy concept, as a study for speaker- independent speech recognition. In this proposed recognition method, training data are divided into several dynamic section and multi-observation sequences which are given proper probabilities by fuzzy rule according to order of short distance from DMSVQ codebook per each section are obtained. Thereafter, the HMM using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. Other experiments to compare with the results of recognition experiments using proposed method are implemented as a data by the various conventional recognition methods under the equivalent environment. Through the experiment results, it is proved that the proposed method in this study is superior to the conventional recognition methods.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.1466-1483
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• 2008

This paper discusses the development of an up-to-date computerized CPT (Cone Penetration Test) based soil engineering classification system to provide geotechnical engineers with a handy tool for their daily design activities. Five CPT soil engineering classification systems are incorporated in this effort. They include the probabilistic region estimation and fuzzy classification methods, both developed by Zhang and Tumay, the Schmertmann, the Douglas and Olsen, and the Robertson et al. methods. In the probabilistic region estimation method, a conformal transformation is used to determine the soil classification index, U, from CPT cone tip resistance and friction ratio. A statistical correlation is established between U and the compositional soil type given by the Unified Soil Classification System (USCS). The soil classification index, U, provides a soil profile over depth with the probability of belonging to different soil types, which more realistically and continuously reflects the in-situ soil characterization, which includes the spatial variation of soil types. The CPT fuzzy classification on the other hand emphasizes the certainty of soil behavior. The advantage of combining these two classification methods is realized through implementing them into visual basic software with three other CPT soil classification methods for friendly use by geotechnical engineers. Three sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the probabilistic region estimation and fuzzy classification methods are cross-correlated with conventional soil classification from borings logs and three other established CPT soil classification methods.

• Transactions of the Korean hydrogen and new energy society
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• v.29 no.4
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• pp.307-316
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• 2018

In this study, the failure mode and effect analysis (FMEA) of hydrogen production process by using the Thermococcus onnurineus NA1 was conducted and advanced methodology to compensate the weakness of previous FMEA methodology was applied. To bring out more quantitative and precise FMEA result for bio-hydrogen production process, fuzzy logic and potential loss cost estimated from ASPEN Capital Cost Estimator (ACCE) was introduced. Consequently, risk for releasing the flammable gases via internal leakage of steam tube which to control the operating temperature of main reactor was caution status in FMEA result without applying the fuzzification and ACCE. Moreover, probability of the steam tube plugging caused by solid property like medium was still caution status. As to apply the fuzzy logic and potential loss cost estimated from ACCE, a couple of caution status was unexpectedly upgraded to high dangerous status since the potential loss cost of steam tube for main reactor and decrease in product gases are higher than expected.