• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.411-418
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• 2000

With the limited amount of budget and time, it is required to determine the priority of investment when there are a large number of hazardous slopes. In this paper, the Rock Slope Risk Rating System is developed based on the combination of the hazard of failure and the damage potential. By applying the proposed rating system to 253 rock slopes in Korean National Highway, it was possible to determine the priority of investment on road cut slopes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1569-1574
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• 2005

In this paper, I propose an intelligent credit rating system using a bankruptcy prediction model based on support vector machines (SVMs). SVMs are promising methods because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle. This study examines the feasibility of applying SVM in Predicting corporate bankruptcies by comparing it with other data mining techniques. In addition. this study presents architecture and prototype of intelligeht credit rating systems based on SVM models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.7-15
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• 2017

Ambient Adjusted line Rating(AAR) method for overhead transmission lines considering Risk Tolerance(RT) was proposed in this paper. AAR is suitable for system operators to plan their operation strategy and maintenance schedule because this can be designed as a seasonal line rating. Several candidate transmission lines are chosen to apply the proposed method in the paper. As a result, it is shown that system reliability was significantly enhanced through maximizing transfer capability, solving the system constraints.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.3
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• pp.227-232
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• 2020

This paper develops a risk index based on an indicator of risk assessment in terms of coastal activity location and accident type. The risk index is derived from a formula which adds the consequence of failure to a vulnerability value, then subtracts the mitigation value. Specifically, the consequence of failure is the number of casualties in coastal activity locations. An indicator of vulnerability refers to coastal environment elements and social elements. A pointer of mitigation includes managerial and organizational elements that indicate the capabilities of coastal activities. A risk rating of coastal activity location is found from a risk matrix consisting of the accident location and type. The purpose of this study is to prevent accidents at coastal activity locations by allowing the Coastal police guard to monitor effectively and inform visitors of potential risks.

• Journal of Applied Reliability
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• v.8 no.4
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• pp.167-179
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• 2008

System risk is the totality of all safety risks to customers, employees, suppliers, and other third parties that arise due to system operations. To assess the risk of major hazards with the potential to cause fatality to the customers and other members of the public, quantitative risk assessment methodologies are used. This paper presents the general principles of risk based management approach to improve the safety of high risk systems such as aviation, railway, and nuclear power plants. For the suitable risk control arrangement, case studies of acceptable risk level, risk rating matrix, and safety management philosophy are presented.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.347-354
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• 1999

The credit rating represents an assessment of the relative level of risk associated with the timely payments required by the debt obligation. In this paper, we present a new approach to credit rating of customers based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of customer information systems representing knowledge gained by experience. The customer information system describes a set of customers by a set of multi-valued attributes, called condition attributes. The customers are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of customers by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the customers analyzed and to derive decision rules from the customer information system which can be used to support decisions about rating new customers. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of the evaluation of credit rating by a department store is studied using the rough set approach.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1358-1371
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• 2017

Dynamic thermal rating (DTR) system is an effective method to improve the capacity of existing overhead line. According to the methodology based on CIGRE (International Council on Large Electric systems) standard, ampacity values under steady-state heating balance can be calculated from ambient environmental conditions. In this study, simulation analysis of relations between parameters and ampacity is described as functional dependence, which can provide an effective basis for the design and research of overhead transmission lines. The simulation of ampacity variation in different rating scales is described in this paper, which are determined from real-time meteorological data and conductor state parameters. To test the performance of DTR in different rating scales, capacity improvement and risk level are presented. And the experimental results show that the capacity of transmission line by using DTR has significant improvement, with low probability of risk. The information of this study has an important reference value to the operation management of power grid.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2007.02a
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• pp.190-196
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• 2007

With the rapid development of electronic commerce, online reputation management systems are of increasing importance in building trust and managing risk. Reputation rating mode and aggregating method are the most crucial parts of a reputation management system. In this paper, we analyze the merits and disadvantages associated with the rating mode and aggregating approach of current reputation management systems, and put forward some suggestions. These suggestions are helpful in improving current reputation management systems and developing new reputation management systems.

• Journal of the Korea Safety Management & Science
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• v.10 no.2
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• pp.71-83
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• 2008

Most researches on the corporate credit rating are generally classified into the area of bankruptcy prediction and bond rating. The studies on bankruptcy prediction have focused on improving the performance in binary classification problem, since the criterion variable is categorical, bankrupt or non-bankrupt. The other studies on bond rating have predicted the credit ratings, which was already evaluated by bond rating experts. The financial institute, however, should perform effective loan evaluation and risk management by employing the corporate credit rating model, which is able to determine the credit of corporations. Therefore, in this study we present a medium sized corporate credit rating system by using Artificial Neural Network(ANN) and Analytical Hierarchy Process(AHP). Also, we developed AHP model for credit rating using non-financial information. For the purpose of completed credit rating model, we integrated the ANN and AHP model using both financial information and non-financial information. Finally, the credit ratings of each firm are assigned by the proposed method.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.199-208
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• 2017

This study investigates the components and rating system of reliable technology credit information for a technology finance donor who is a consumer of the information and aims to create an effective and optimal technology credit appraisal system to enlarge technology finance supply. Firstly, we calculate the optimal TCAR which becomes the maximum AUROC through the combination of ratio change, verify the substitution possibility between TAR and CR through the existing CR and system gap simulation, and propose a rating system by which financial institutes can utilize the TCAR as a credit rating. As a result, 70% : 30% is the most suitable as the weighted combination ratio of credit rating : technology rating. As a result of this study, we confirmed the possibility that the technical credit rating information could be substituted by the credit rating or the technology appraisal rating. Furthermore, it also suggests that sophisticated risk management is possible through using technology credit rating that are combined with credit and technology appraisal rating.