• Journal of Information Processing Systems
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• v.15 no.3
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• pp.655-669
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• 2019

Supplier evaluation is of great significance in green supply chain management. Influenced by factors such as economic globalization, sustainable development, a holistic index framework is difficult to establish in green supply chain. Furthermore, the initial index values of candidate suppliers are often characterized by uncertainty and incompleteness and the index weight is variable. To solve these problems, an index framework is established after comprehensive consideration of the major factors. Then an adaptive weight D-S theory model is put forward, and a fuzzy-rough-sets-AHP method is proposed to solve the adaptive weight in the index framework. The case study and the comparison with TOPSIS show that the adaptive weight D-S theory model in this paper is feasible and effective.

• Journal of Digital Convergence
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• v.12 no.6
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• pp.215-221
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• 2014

The Fingerprint recognition system is a system which identify the user's identify by verifying user's fingerprint and prepared data. The performance of fingerprint recognition system is dependent on 'fingerprint recognition time' and 'fingerprint recognition accuracy' and so on. In this paper, we developed a evaluation model about efficiency based on ISO quality evaluation standard for evaluating of quality level of fingerprint recognition system. We expect to contribute to construct and use of evaluation criteria based on quality evaluation standard by this study.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.59-65
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• 2019

In this paper, we propose a software quality measurement metrics of ISO / IEC 25023, which is newly proposed for software quality evaluation, to compare the difference with ISO / IEC 9126-2 which was used for software quality evaluation. In this paper, we propose a method for evaluating the quality of reliability based on the software reliability growth model among the eight quality characteristics presented in ISO / IEC 25023. Based on ISO / IEC 25023, software-quality evaluations demonstrate that there is some risk in evaluating reliability when based on data.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.6
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• pp.437-452
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• 2002

The Metropolitan Tracer Experiment (METREX) was performed over the Washington, D.C. area using two inert, non-deposition perfluorocarbon gases for over 1 year period (November 1983∼December 1984). Two perfluorocarbon gas tracers (PDCH, PMCH) were released simultaneously at intervals of every 36 hours for 6 hours, regardless of the meteorological conditions in metropolitan area. Samples were collected continuously for 8 hours at a central downtown and two adjacent suburban locations. Monthly air samples were collected at 93 sites across the whole region (at urban, suburban, and rural locations). The purpose of this study is to simulate INPUFF and ISCST model using METREX data, and to compare calculated and observed concentrations. In the case of INPUFF simulation, two meteorological input data were used. One is result data from wind field model which was calculated by diagnostic wind model (DWM), the other is meteorological data observed at single station. Here, three kinds of model calculation were performed during April and July 1984; they include (1) INPUFF model using DWM data (2) INPUFF model using single meteorological data (3) ISCST model. The monthly average concentration data were used for statistic analysis and to draw their horizontal distribution patterns. Eight-hour-averaged concentration was used to describe movement of puff during the episode period. The results showed that the concentrations calculated by puff model (INPUFF) were better than plume model (ISCST). In the case of puff model (INPUFF), a model run using wind field data produced better results than that derived by single meteorological data.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2002.10b
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• pp.249-250
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• 2002

In this paper, the relationship among the 3-D surface topography parameters are studied. Several surface topography parameters that are important in tribology are calculated against various surface topography data. 3-D surface data with desired properties are generated by using the non-causal 2-D auto-regressive (AR) model. The non-causal 2-D AR model is a random 3-D surface topography model that can generate 3-D surface topography data with specified parameters.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.435-445
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• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.

• Geomechanics and Engineering
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• v.30 no.3
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• pp.313-324
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• 2022

With the development of the economy, people's utilization of underground space are also improved, and a large number of cities have begun to build subways to relieve traffic pressure. The choice of subway station construction method is crucial. If an inappropriate construction method is selected, it will not only waste costs but also cause excessive deformation that may also threaten construction safety. In this paper, a subway station construction scheme selects model based on the AHP-fuzzy comprehensive evaluation. The rationality of the model is verified using numerical simulation and monitoring measurement data. Firstly, considering the economy and safety, a comprehensive evaluation system is established by selecting several indicators. Then, the analytic hierarchy process is used to determine the weight of the evaluation index, and the dimensionless membership in the fuzzy comprehensive evaluation method is used to evaluate the advantages and disadvantages of the construction method. Finally, the method is applied to Liaoyang east road station of Qingdao metro Line 2, and the results are verified by numerical simulation and monitoring measurement data. The results show that the model is scientific, practical and applicable.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.7
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• pp.55-63
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• 2006

Bacterial transport models were evaluated in this study to determine the suitable model at describing bacterial transport in saturated column experiments. Four models used in the evaluation were: advective-dispersive equation (ADE) + equilibrium sorption/retardation (ER) + kinetic reversible sorption (KR) (Model I), ADE + two-site sorption (Model 2), ADE + ER + kinetic irreversible sorption (KI) (Model 3), ADE + KR + KI (Model 4). Firstly, analyses were performed with the first experimental data, showing that Model 4 is appropriate for describing bacterial transport. Even if Model 1 and 2 fit well to the observed data, they have a defect of not including the irreversible sorption, which is directly related to mass loss of bacteria. Model 3 can not properly describe the tailing observed in the data. However, further analysis with the second data indicates that Model 4 can not describe retardation of bacteria, even if the sorption-related parameters are varied. Therefore, Model 4 is modified by incorporating retardation factor into the model, resulting in the improved fitting to the data. It indicates that the transport model, into which retardation, kinetic reversible sorption, and kinetic irreversible sorption are incorporated, is suitable at describing bacterial transport in saturated column experiments. It is expected that the selected transport model could be applied to properly analyze the bacterial transport in saturated porous media.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.705-712
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• 2003

In this paper, we propose new unified methodologies of reliability and its cost evaluation in power distribution systems. The unified method means that the proposed reliability approaches consider both conventional evaluation factor, i.e. sustained interruptions and additional ones, i.e. momentary interruptions and voltage sags. Because the three voltage quality phenomena generally originate from the outages on distribution systems, the basic and additional reliability indices are summarized considering the fault clearing mechanism. The proposed unified method is divided into the reliability evaluation for calculating the reliability indices and reliability cost evaluation for assessing the damage of customer. The analytic and probabilistic methodologies are presented for each unified reliability and its cost evaluation. The time sequential Monte Carlo technique is used for the probabilistic method. The proposed DVL(Demand Varying Load) model is added to the reliability cost evaluation substituting the average load model. The proposed methods are tested using the modified RBTS(Roy Billinton Test System) form and historical reliability data of KEPCO(Korea Electric Power Corporation) system. The daily load profile of the each customer type in domestic are gathered for the DVL model. Through the case studies, it is verified that the proposed methods can be effectively applied to the distribution systems for more detail reliability assessment than conventional approaches.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.47-61
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• 2023

Satisfaction on the residential environment is a major factor influencing the choice of residence and migration, and is directly related to the quality of life in the city. As online services of real estate increases, people's evaluation on the residential environment can be easily checked and it is possible to analyze their satisfaction and its determining factors based on their evaluation. This means that a larger amount of evaluation can be used more efficiently than previously used methods such as surveys. This study analyzed the residential environment reviews of about 30,000 apartment residents collected from 'Zigbang', an online real estate service in Seoul. The apartment review of Zigbang consists of an evaluation grade on a 5-point scale and the evaluation content directly described by the dweller. At first, this study labeled apartment reviews as positive and negative based on the scores of recommended reviews that include comprehensive evaluation about apartment. Next, to classify them automatically, developed a model by using Bidirectional Encoder Representations from Transformers(BERT), a deep learning-based natural language processing model. After that, by using SHapley Additive exPlanation(SHAP), extract word tokens that play an important role in the classification of reviews, to derive determining factors of the evaluation of the residential environment. Furthermore, by analyzing related keywords using Word2Vec, priority considerations for improving satisfaction on the residential environment were suggested. This study is meaningful that suggested a model that automatically classifies satisfaction on the residential environment into positive and negative by using apartment review big data and deep learning, which are qualitative evaluation data of residents, so that it's determining factors were derived. The result of analysis can be used as elementary data for improving the satisfaction on the residential environment, and can be used in the future evaluation of the residential environment near the apartment complex, and the design and evaluation of new complexes and infrastructure.