• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.55-62
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.421-436
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the deng's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(Wen's GRG & weighted mean) method is the best of any other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.647-654
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• 2016

In the defense industry, national security takes priority over economic sense and this has translated into high cost and long-term research and development. However, the exponential growth of technology and rapid changes in the security situation in recent years have resulted in a call for the development of systems at a low cost within a short period of time. In order to implement a modularization strategy in the field of defense, the introduction of line replaceable units in OO systems needs to be prioritized. This study selects six criteria following a literature review and prioritizes 11 modules for OO systems using the project evaluation method, Grey Relational Analysis (GRA). Based on the GRA results, the grey relational grades were derived as 0.83, 0.81 and 0.80 for the M11 (Main board), M8 (EMI module), M3 (Single board computer) modules, respectively. The cost and time of development is expected to be reduced in accordance with the grey relational grade. The results of this research could be utilized for decision making on adopting modularization in similar system development or product improvement programs (PIPs).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.139-145
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• 2004

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities. The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the, methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

• Journal of Navigation and Port Research
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• v.44 no.4
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• pp.291-297
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• 2020

In recent years, an increase in deaths and injuries of port cargo handling workers, has raised the need for more effective accident management. The purpose of this study was to evaluate the accident risk for port cargo handling workers and assess ports with high accident risk within the Korean alternative ports using the Entropy & GRA (Grey Relational Analysis). To achieve this purpose, first, 11 Korean ports were selected and the evaluative factors for their outranking evaluation by brainstorming were extracted. Second, the Grey Relational Coefficient of 11 alternative ports was calculated using the GRA. This paper, finally, determined the priority orders of accident risk through calculation of the Grey Relational Grade as the link Grey Relational Coefficient method and the weights of the evaluative factors were calculated by using the Entropy method. In the proposed model, eight criteria such as cargo worker, old cargo worker, work hours, facilities environment, steel cargo volumes, cargo volumes, injury numbers, and death numbers were collected. Busan port was identified as highest accident risk port, and so it should be a top priority to develop a plan to mitigate the risk.

• Geomechanics and Engineering
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• v.8 no.5
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• pp.631-647
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• 2015

Engineers may encounter unpredictable cavities, sinkholes and karst conduits while tunneling in karst area, and water inrush disaster frequently occurs and endanger the construction safety, resulting in huge casualties and economic loss. Therefore, an optimal classification method based on grey system theory (GST) is established and applied to accurately predict the occurrence probability of water inrush. Considering the weights of evaluation indices, an improved formula is applied to calculate the grey relational grade. Two evaluation indices systems are proposed for risk assessment of water inrush in design stage and construction stage, respectively, and the evaluation indices are quantitatively graded according to four risk grades. To verify the accuracy and feasibility of optimal classification method, comparisons of the evaluation results derived from the aforementioned method and attribute synthetic evaluation system are made. Furthermore, evaluation of engineering practice is carried through with the Xiakou Tunnel as a case study, and the evaluation result is generally in good agreement with the field-observed result. This risk assessment methodology provides a powerful tool with which engineers can systematically evaluate the risk of water inrush in karst tunnels.