• Journal of Information Processing Systems
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• v.18 no.4
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.1061-1072
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• 2005

A hydrological grey model is developed to forecast short-term river runoff from the Naju watershed located at upstream of the Youngsan estuary dam in Korea. The runoff of the Naju watershed is measured in real time at the Naju streamflow gauge station, which is a key station for forecasting the upstream inflow and operating the gates of the estuary dam in flood period. The model's governing equation is formulated on the basis of the grey system theory. The model parameters are reparameterized in combination with the grey system parameters and estimated with the annealing-simplex method In conjunction with an objective function, HMLE. To forecast accurately runoff, the fifth order differential equation was adopted as the governing equation of the model in consideration of the statistic values between the observed and forecast runoff. In calibration, RMSE values between the observed and simulated runoff of two and six Hours ahead using the model range from 3.1 to 290.5 $m^{3}/s,\;R^2$ values range from 0.909 to 0.999. In verification, RMSE values range from 26.4 to 147.4 $m^{3}/s,\;R^2$ values range from 0.940 to 0.998, compared to the observed data. In forecasting runoff in real time, the relative error values with lead-time and river stage range from -23.4 to $14.3\%$ and increase as the lead time increases. The results in this study demonstrate that the proposed model can reasonably and efficiently forecast runoff for one to six Hours ahead.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.61-73
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• 2009

To efficiently carry out the flood management of a multipurpose dam, two flood forecasting models are developed, each of which has the capabilities of forecasting upstream inflows and flood discharges downstream of a dam, respectively. The models are calibrated, validated, and evaluated by comparison of the observed and the runoff forecasts upstream and downstream of Namgang Dam. The upstream inflow forecasting model is based on the Grey system theory and employs the sixth order differential equation. By comparing the inflows forecasted by the models calibrated using different data sets with the observed in validation, the most appropriate model is determined. To forecast flood discharges downstream of a dam, a Grey model is integrated with a modified Muskingum flow routing model. A comparison of the observed and the forecasted values in validation reveals that the model can provide good forecasts for the dam's flood management. The applications of the two models to forecasting floods in real situations show that they provide reasonable results. In addition, it is revealed that to enhance the prediction accuracy, the models are necessary to be calibrated and applied considering runoff stages; the rising, peak, and falling stages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.2178-2184
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• 2015

With the development of wireless network technologies, mobile users may use various networks easily and expect more advanced services. On the other hand, it may bring on some problems with network resource management that should lead the service provider to improve the current service quality and manage the network resource efficiently. This paper proposes the optimized radio resource management (RRM) scheme that integrates the Grey Relational Analysis (GRA) and game theory. The first applies the GRA to determine the Grey Relation Coefficient (GRC) factors that represent the network preference, and the network provider then selects the requested service that provide maximum payoff through Nash Equilibrium. Six requested services that have one application service among four different types of service classes were considered and the game was played repeatedly. In WiMAX, WLAN 1 and WLAN 2 game, the maximum payoff of each players was 93, 90.6 and 92.8 respectively. The experimental results show that every requested service can be selected by the network provider. Consequently, the proposed radio resource management mechanism is more effective in heterogeneous wireless networks.

• Computers and Concrete
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• v.26 no.2
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• pp.175-183
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• 2020

Fly ash has become an important component of concrete as supplementary cementitious material with the development of concrete technology. To make use of fly ash efficiently, four types of fly ash with particle size distributions that are in conformity with four functions, namely, S.Tsivilis, Andersen, Normal and F distribution, respectively, were prepared. The four particle size distributions as functions of the strength and pore structure of concrete were thereafter constructed and investigated. The results showed that the compressive and flexural strength of concrete with the fly ash that conforming to S.Tsivilis, Normal, F distribution increased by 5-10 MPa and 1-2 MPa, respectively, compared to the reference sample at 28 d. The pore structure of the concrete was improved, in which the total porosity of concrete decreased by 2-5% at 28 d. With regarding to the fly ash with Andersen distribution, it was however not conducive to the strength development of concrete. Regression model based on the grey multiple linear regression theory was proved to be efficient to predict the strength of concrete, according to the characteristic parameters of particle size and pore structure of the fly ash.

• Journal of Distribution Science
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• v.11 no.9
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• pp.35-42
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• 2013

Purpose - The objective of this paper is to identify how different incentive factors influence teachers with different ages and professional titles at LinYi University, China. Research design, data, and methodology - A total of 435 university teachers participated in the study, and the Grey Correlation Degree Analysis method was used to analyze the sample data. Results - The results indicated that teachers with different professional titles and ages have different levels of preference on various incentive factors. Young and assistant-level teachers seem to place more importance on incentives than associate and senior-level teachers. Conclusions - This study has some practical implications. First, the principal and school administrators should pay more attention to young and middle-aged teachers and to how these teachers are motivated through monetary incentives as compared to associate or senior-level teachers. Second, school administrators should pay more attention to teachers' opportunities for career growth and should provide more opportunity for academic promotion. In order to stimulate positivity in teachers, school administrators should adopt various incentive systems.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.37-47
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• 2010

This research is aimed at comprehensively evaluating the condition of a road surface of a highway in satisfaction of its users. This research conducted an overall evaluation of a road surface condition by adding qualitative data, or a driver's satisfaction to the existing quantitative elements, whereas the existing research put its focus on a correlation analysis with quantitative factors and qualitative factors through a statistical method. As for an evaluation method, this research conducted an overall evaluation by using Grey System Theory which makes possible an integrated evaluation. The analyzed results make it possible to diagnose the current conditions of each section of object roads and to predict the potentially changeable conditions for the time to come. In addition, these analyzed results could hopefully be applied to the maintenance of freeways through diverse methods. It is hoped that the evaluation of a road surface condition of a highway in satisfaction of its user could be helpful to keeping up the satisfaction of a driver and passenger on the highway by more than a certain level. In addition, the analyzed data on the influence of data value observed by comprehensively evaluating a variety of elements could be used as a secondary means of the decision-making process in relation to road maintenance. On top of that, it could be used as a means of improving road maintenance system and offering the improved driving environment of the highway.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.75-84
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• 2012

PURPOSES : This paper aims to improve the evaluation method of the Level of Service(LOS) for urban streets presented by the current Korean Highway Capacity Manual(KHCM) and suggest its utilization plan as a part of the methods to evaluate the sustainability of a transportation policy. METHODS : This paper carried out a research in 3 steps to develop a new evaluation method. First of all, this paper reviewed the previous studies related to the LOS of urban streets and the socially requested items for a sustainable transportation system. Then this paper derived an index and weight through expert questions to select an evaluation index. Lastly, this paper compared the results according to the existing evaluation methods with the new evaluation methods through case studies. This paper used an Analytic Hierarchy Process(AHP) for importance analysis and weight selection between new evaluation items and indices, and applied a Grey System Theory(GST) for a synthetic and integrated evaluation between the selected evaluation indices. RESULTS : As a result of evaluating the LOS according to the existing evaluation methods and the integrated evaluation methods using a GST through case studies, it was analyzed that new methods' results are less than or equal to the existing evaluation methods; and as a result of applying a weight between evaluation indices according to AHP, it was noticed that the total score seems to rise more when the LOS in the existing evaluation is calculated lower. It was analyzed that the LOS calculated by reflecting the newly established evaluation items and the importance between indices in this study has difference from the LOS of the existing urban streets. CONCLUSIONS : It is expected that this evaluation method can diagnose the current conditions when establishing a future sustainable traffic system and can be used for the measurement of the sustainability effects of the improvement plans and so on.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.49-57
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• 2021

In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.