• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.752-757
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• 2014

This paper attempts to evaluate the impact of power plant penetration on constraints of a transmission network and proposes a methodology based on risk level, which can evaluate the condition of the network and facilities intuitionally. Furthermore, based on this methodology, RLII(Risk Level Improvement Index) is proposed in order to establish comprehensive TNEP(Transmission Network Expansion Planning) from a viewpoint of ISO(Independent System Operator). In order to verify the proposed methods in this paper, real power systems in Incheon and Shiheung areas, south Korea are applied to the case study.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1173-1183
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• 2016

In this paper, we proposed an information security risk index to diagnose users' malware infection situations (such as computer virus and adware) by gathering data from KT network systems. To develop the information security risk index, we used the analytic hierarchy process methodology and estimated the risk weights of malware code types using the judgments of experts. The control chart could be used effectively to forecast the information security risk for the proposed information security risk index data.

• Journal of Navigation and Port Research
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• v.41 no.5
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• pp.287-296
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• 2017

The Formal Safety Assessment (FSA) is a structured and systematic methodology developed by the IMO, aimed at assessing the risk of vessels and recommending the method to control intolerable risks, thereby enhancing maritime safety, including protection of life, health, the marine environment and property, by using risk analysis and cost-benefit assessment. While the FSA has mostly been applied to merchant vessels, it has rarely been applied to a DP vessel, which is one of the special purpose vessels in the offshore industry. Furthermore, most of the FSA has been conducted so far by using the Fault Tree Analysis tool, even though there are many other risk analysis tools. This study carried out the FSA for safe operation of DP vessels by using the Bayesian network, under which conditional probability was examined. This study determined the frequency and severity of DP LOP incidents reported to the IMCA from 2001 to 2010, and obtained the Risk Index by applying the Bayesian network. Then, the Risk Control Options (RCOs) were identified through an expert brainstorming and DP vessel simulations. This study recommends duplication of PRS, regardless of the DP class and PRS type and DP system specific training. Finally, this study verified that the Bayesian network and DP simulator can also serve as an effective tool for FSA implementation.

• Journal of the Korea Society for Simulation
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• v.21 no.4
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• pp.91-102
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• 2012

Network port scan attack is the method for finding ports opening in a local network. Most existing IDSs(intrusion detection system) record the number of packets sent to a system per unit time. If port scan count from a source IP address is higher than certain threshold, it is regarded as a port scan attack. The degree of risk about source IP address performing network port scan attack depends on attack count recorded by IDS. However, the measurement of risk based on the attack count may reduce port scan detection rates due to the increased false negative for slow port scan. This paper proposes a method of summarizing 4 types of information to differentiate network port scan attack more precisely and comprehensively. To integrate the riskiness, we present a risk index that quantifies the risk of port scan attack by using PCA. The proposed detection method using risk index shows superior performance than Snort for the detection of network port scan.

• The Journal of Society for e-Business Studies
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• v.20 no.2
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• pp.125-140
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• 2015

It is general that the impact of supply chain risk spread out to the whole network along the connected structure. Due to the risk propagation the probability to exposure a certain risk is affected by not only the characteristics of each risk factor but also network structure. It means that the structural connectivity among vertices should be considered while designing supply chain network in order to minimize disruption cost. In this research, the betweenness centrality has been utilized to quantitatively assess the structural vulnerability. The betweenness centrality is interpreted as the index which can express both the probability of risk occurrence and propagation of risk impact. With the structural vulnerability index, it is possible to compare the stability of each alternative supply chain structure and choose the better one.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.

• Journal of Navigation and Port Research
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• v.33 no.1
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• pp.9-19
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• 2009

This paper describes empirical approach methodology for the quantitative risk assessment of maritime transportation accident (MTA) of a merchant ship. The principal aim of this project is to estimate the risk of MTA that could degrade the ship safety by analyzing the underlying factors contributing to MTA based on the IMO's Formal Safety Assessment techniques and, by assessing the probabilistic risk level of MTA based on the quantitative risk assessment methodology. The probabilistic risk level of MTA to Risk Index (RI) composed with Probability Index (PI) and Severity Index (SI) can be estimated from proposed Maritime Transportation Accident Model (MTAM) based on Bayesian Network with Bayesian theorem Then the applicability of the proposed MTAM can be evaluated using the scenario group with 355 core damaged accident history. As evaluation results, the correction rate of estimated PI, $r_{Acc}$ is shown as 82.8%, the over ranged rate of PI variable sensitivity with $S_p{\gg}1.0$ and $S_p{\ll}1.0$ is shown within 10%, the averaged error of estimated SI, $\bar{d_{SI}}$ is shown as 0.0195 and, the correction rate of estimated RI, $r_{Acc}$(%), is shown as 91.8%. These results clearly shown that the proposed accident model and methodology can be use in the practical maritime transportation field.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.1789-1794
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• 2014

This paper suggests an application method for a superconducting fault current limiter (SFCL) using an evaluation index to estimate the risk regarding the short-circuit capacity of the circuit breaker (CB). Recently, power distribution systems have become more complex to ensure that supply continuously keeps pace with the growth of demand. However, the mesh or loop network power systems suffer from a problem in which the fault current exceeds the short-circuit capacity of the CBs when a fault occurs. Most case studies on the application of the SFCL have focused on its development and performance in limiting fault current. In this study, an analysis of the application method of an SFCL considering the risk of the CB's short-circuit capacitor was carried out in situations when a fault occurs in a loop network power system, where each line connected with the fault point carries a different current that is above or below the short-circuit capacitor of the CB. A loop network power system using PSCAD/EMTDC was modeled to investigate the risk ratio of the CB and the effect of the SFCL on the reduction of fault current through various case studies. Through the risk evaluations of the simulation results, the estimation of the risk ratio is adequate to apply the SFCL and demonstrate the fault current limiting effect.

• The Journal of Industrial Distribution & Business
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• v.13 no.10
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• pp.1-8
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• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1154-1162
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• 2014

In the restructured electricity market, Performance-Based Regulation (PBR) regime has been introduced to the distribution network. To ensure the network stability, this regime is used along with quality regulations. Quality regulation impose new financial risks on distribution system operators (DSOs). The poor quality of the network will result in reduced revenues for DSOs. The mentioned financial risks depend on the quality indices of the system. Based on annual variation of these indices, the cost of quality regulation will also vary. In this paper with regard to reclosing fault in distribution network, we develop a risk-based method to assess the financial risks caused by quality regulation for DSOs. Furthermore, in order to take the stochastic behavior of the distribution network and quality indices variations into account, time-sequential Monte Carlo simulation method is used. Using the proposed risk method, the effect of taking reclosing time into account will be examined on system quality indicators and the cost of quality regulation in Swedish rural reliability test system (SRRTS). The results show that taking reclosing fault into consideration, affects the system quality indicators, particularly annual average interruption frequency index of the system (SAIFI). Moreover taking reclosing fault into consideration also affects the quality regulations cost. Therefore, considering reclosing time provides a more realistic viewpoint about the financial risks arising from quality regulation for DSOs.