• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.29-35
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• 2021

In this paper, we propose a method that combines KNN(K-Nearest Neighbor), Local Map Classification and Bayes Filter as a way to increase the accuracy of location positioning. First, in this technique, Local Map Classification divides the actual map into several clusters, and then classifies the clusters by KNN. And posterior probability is calculated through the probability of each cluster acquired by Bayes Filter. With this posterior probability, the cluster where the robot is located is searched. For performance evaluation, the results of location positioning obtained by applying KNN, Local Map Classification, and Bayes Filter were analyzed. As a result of the analysis, it was confirmed that even if the RSSI signal changes, the location information is fixed to one cluster, and the accuracy of location positioning increases.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.91-97
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• 2021

This paper uses a data extension technique originally designed for the rule refinement problem to handling incomplete data. This technique is characterized in that each event can have a weight indicating importance, and each variable can be expressed as a probability value. Since the key problem in this paper is to find the probability that is closest to the missing value and replace the missing value with the probability, three different algorithms are used to find the probability for the missing value and then store it in this data structure format. And, after learning to classify each information area with the SVM classification algorithm for evaluation of each probability structure, it compares with the original information and measures how much they match each other. The three algorithms for the imputation probability of the missing value use the same data structure, but have different characteristics in the approach method, so it is expected that it can be used for various purposes depending on the application field.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.124-129
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• 2003

As the power industry moves towards open competition, there has been a call for methodology to evaluate power system reliability by using composite interruption cost. This paper presents algorithms to evaluate the interruption cost of distribution power systems by taking into consideration the failure source and the composite customer interruption cost. From the consumer's standpoint, the composite customer interruption cost is considered as the most valuable index to estimate the reliability of a power distribution system. This paper presents new algorithms that take into account the load by customer type and failure probability by distribution facilities while calculating the amount of unserved energy by customer type. Finally, evaluation results of unserved energy and system interruption cost based on composite customer interruption cost are shown in detail.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.305-309
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• 2010

The buckling behavior of CWR tracks is affected by the various parameters such as stiffness and geometry of track panel, ballast resistance, rail temperature, initial imperfection, and wheel load. Until now, CWR tracks were managed by the dichotomous logic (deterministic approach) despite these influence factors are having the nature of random variables. So, the design method and existing management process to prevent the track buckling can be very non-economic since the value of these influence factors to calculate the track buckling strength are selected by considering the worst track condition. In this study, buckling probability evaluation process is proposed which is based on the reliability index, AFOSM method, and limit state equation.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.16-23
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• 2006

Recently the design of multi-stage gear drive is being highly concerned. Until now, since the researches of gear drive are focused on the design for satisfying safety factor, the reliability evaluation of multi-stage gear drive is not included. In this paper, the life and reliability models of multi-stage gear drive are proposed using methods of probability and statistics. The life and reliability of the multi-stage gear drive have been evaluated, which is based on the life and reliability of each stage gear drive. The pinion and gear lives of each stage are calculated using the Lundberg-Palmgren theory and the Weibull failure distribution. These lives are combined using methods of probability and statistics to produce a life and reliability model of multi-stage gear drive.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.459-464
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• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Computational Structural Engineering : An International Journal
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• v.2 no.1
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• pp.1-10
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• 2002

Information on the distribution of the basic random variables is essential for the accurate evaluation of structural reliability. The usual method for determining the distribution is to fit a candidate distribution to the histogram of available statistical data of the variable and perform appropriate goodness-of-fit tests. Generally, such candidate distributions would have two parameters that may be evaluated from the mean value and standard deviation of the statistical data. In the present paper, a-parameter Gamma distribution, whose parameters can be directly defined in terms of the mean value, standard deviation and skewness of available data, is suggested. The flexibility and advantages of the distribution in fitting statistical data and its significance in structural reliability evaluation are identified and discussed. Numerical examples are presented to demonstrate these advantages.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.177-183
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• 1999

This paper presents how to evaluate the transformer damage caused by reclosing scheme at the distribution substation. We describe a quantitative relationship between the reclosing scheme and the number of fault current flowing through transformer wsing the probability of a reclosing success/failure. The transformer damage from reclosing scheme is presented using a weight function and a damage function. A weight function is associated with the number of reclosing attempts and the reclosing deadtime to consider cumulative stress caused by reclosing scheme. A damage function is associated with a transformer impact ratio and a transformer functional life. In the case study, the transformer damage is simulated for the probability of a reclosing success. And the evaluation of transformer damage using KEPCO's operation data is performed.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.458-466
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• 2012

We have developed a weapon effectiveness evaluation model for top-attack smart munitions(WEEM/TASM), which is a many on many Monte Carlo Model evaluating the effectiveness of top-attack smart munitions against armoured ground vehicles. In this model the battle is reduced to a one-sided battle situation in that the target vehicles are regarded as being stationary and passive. It can simulate the whole attack process of smart munitions from firing artillery dispenser to sensing and hitting processes after dispense. It can also calculate the probability of kill of each target and the numbers of rounds required to fulfill the degree of damage in statistical manners. In this paper, we describe the basis for our design concepts reflected in the model to simulate the weapon effectiveness of top-attack smart munitions and provide simulation results for an example case.

• KIEE International Transactions on Power Engineering
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• v.5A no.3
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• pp.286-292
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• 2005

As the power industry moves towards open competition, there has been a call for methodology to evaluate power system reliability by using composite interruption cost. This paper presents algorithms to evaluate the interruption cost of distribution power systems by taking into consideration the failure source and the composite customer interruption cost. From the consumer's standpoint, the composite customer interruption cost is considered as the most valuable index to estimate the reliability of a power distribution system. This paper presents new algorithms that consider the load by customer type and failure probability by distribution facilities while calculating the amount of unserved energy by customer type. Finally, evaluation results of unserved energy and system interruption cost based on composite customer interruption cost are shown in detail.