• Journal of Korean Institute of Industrial Engineers
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• v.37 no.4
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• pp.358-366
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• 2011

Multi-criteria ABC inventory classification, which aims to classify inventory items by considering more than one criterion, is one of the most widely employed techniques for inventory control. The weighted linear optimization (WLO) model proposed by Ramanathan (2006) solves the problem of multi-criteria ABC inventory classification by generating a set of criterion weights for each inventory item and assigning a normalized score to the item for ABC analysis. However, the WLO model has some limitations. First, many inventory items can share the same optimal score, which can hinder a precise classification of inventory items. Second, the model allows too much flexibility in weighting multiple criteria; each item is allowed to choose its own weights so that it can maximize its score. As a result, if an item dominates the others in terms of a certain criterion, it may be classified into a higher class regardless of other criteria by assigning an overwhelming weight to the criterion. Consequently, an item with a high value in an unimportant criterion and low values in others may be inappropriately classified as class A, leading to an inaccurate classification of inventory items. To overcome these shortcomings, we extend the WLO model by using the cross-efficiency method in data envelopment analysis. We claim that the proposed model can provide a more reasonable and accurate classification of inventory items by mitigating the adverse effect of flexibility in the choice of weights and yielding a unique ordering of inventory items.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.245-269
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• 2004

While the role of local community is getting important in reducing greenhouse gases, current financial supports have not considered these efforts. Instead, development activities have been the only basis of fiscal distribution, which have led to unsustainable development. In this context, this paper analyzes the emission and absorb of air pollutants by local districts in Daegu Metropolitan city and constructs an empirical energy database for local energy use and environmental emissions. Based on the data, it prioritized environmental contribution by region through using MCDM methods, that include maximin & maximax method, simple additive weighting (SAW) and hierarchical additive weighting method (HAW). This concludes the possibility of policy methodology through which we can input environmental variables in distributing local budget.

• Journal of Korean Society of Rural Planning
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• v.19 no.3
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• pp.107-116
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• 2013

In this study, it provides the diagnostic index for the rural landscape formation. For the development of diagnostic index, this study first analyzed documents and papers on the landscape formation. Landscape types are also classified by their function and then landscape index was developed by AHP method. Classification system was categorized as three steps: 2 items for 1st step, 10 items for 2nd step, and 20 items(criteria) for 3rd step. In the survey of weighting values with AHP method, the analysis result for the first step showed that rural village landscape is more important than landscape around the village by approximately 20%. In the second step, residence is rated as the most important, followed by village tree planting, and then farmland around the rural villages, greenery, and water environment. In the third step, the feng shui is rated as the most important, followed by tree planting, village forest, culture, and history. While vehicle maintenance, village alleys and pedestrian facilities are rated lower. In index of the around the village, weighting value for index of the farm land and skyline has the highest value. While species richness, water quality and water resources were rated relatively low. In the future, the rural landscapes diagnosis index will be applied to measure the level of the rural villages landscapes and it is expected to propose political support for the landscapes formation.

• Journal of Korean Society of Steel Construction
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• v.9 no.3 s.32
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• pp.457-465
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• 1997

The Shape optimization makes it possible to reduce the weight of structure and cost then member sizing optimization. A vast amount of imprecise information is existed in constraints of the optimum design. It is very difficult and sometimes confusing to describe and to deal with the several criteria which contain fuzzy degrees of relatives importance. This paper proposed weighting strategies in the multiobjective shape optimization of fuzzy structural system by ${\alpha}$-cut approach. The algorithm in this research is numerically tested for 2-bar truss structure. The result show that. the user can choose the one optimum solution in practices as obtaining the optimum solutions according to the ${\alpha}$-cut approach, weight of volume and displacement.

• Journal of the Korean Society for information Management
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• v.18 no.2
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• pp.203-230
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• 2001

The purpose of this study is to develop a document clustering model for automatic classification of knowledge. Two test collections of newspaper article texts and journal article abstracts are built for the clustering experiment. Various feature reduction criteria as well as term weighting methods are applied to the term sets of the test collections, and cosine and Jaccard coefficients are used as similarity measures. The performances of complete linkage and K-means clustering algorithms are compared using different feature selection methods and various term weights. It was found that complete linkage clustering outperforms K-means algorithm and feature reduction up to almost 10% of the total feature sets does not lower the performance of document clustering to any significant extent.

• Structural Engineering and Mechanics
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• v.89 no.2
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• pp.213-223
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• 2024

This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

• Magazine of the Korean Society of Agricultural Engineers
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• v.26 no.3
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• pp.35-45
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• 1984

Generally speaking, agriculture exist in a climatic environment of uncertainty. Namely, normal rainfall value, as given by the mean values, does not exist. Thought on exists, itl does not affect like extreme Precipitation value on the part of agriculture and of others. Therefore, it is important that we measure the duration and severity index of drought caused by extreme precipitation deficit. In this purpose, this study was dealt with the calculation of drought duration and severity indexs by the method of monthly weighting coefficient. There is no quantitive definition of drought that is universally acceptable. Most of the criteria was used to identify drought have been arbitrary because a drought is a 'non-event' as opposed to a distinct event such as a flood. Therefore, confusion arises when an attempt is made to define the drought phenomenon, the calculation of duration, drought index is based on the following four fundamental question, and this study was dealt with the answers of these four questions as they related to this analytical method, as follows. First, the primary interest in this study is to be the lack of precipitation as it relates to agricultural effective rainfall. Second, the time interval was used to be month in this analysis. Third, Drought event, distinguished analytically from other event, is noted by monthly weighting coefficient method based on monthly rainfall data. Fin-ally, the seven regions used in this study have continually affected by drought on account of their rainfall deficit. The result from this method was very similar to the previous papers studied by many workers. Therefore, I think that this method is very available in Korea to identify the duration of drought, the deficit of precipitation and severity index of drought, But according to the climate of Korea exist the Asia Monsoon zone. The monthly weighting coefficient is modify a little, Because get out of 0.1-0.4 occasionally.

• Analytical Science and Technology
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• v.34 no.6
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• pp.241-250
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• 2021

Calibration curves are essential in quantitative methods and for improving the accuracy of analyte measurements in biological samples. In this study, a statistical analysis model built in the R language (The R Foundation for Statistical Computing) was used to identify a set of weighting factors and regression models based on a stepwise selection criteria. An LC-MS/MS method was used to detect the presence of urinary methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹ -tetrahydrocannabinol in a sample set. Weighting factors for the calibration curves were derived by calculating the heteroscedasticity of the measurements, where the presence of heteroscedasticity was determined via variance tests. The optimal regression model and weighting factor were chosen according to the sum of the absolute percentage relative error. Subsequently, the order of the regression model was calculated using a partial variance test. The proposed statistical analysis tool facilitated selection of the optimal calibration model and detection of methamphetamine, amphetamine, and 11-nor-9-carboxy-Δ⁹-tetrahydrocannabinol in urine. Thus, this study for the selection of weighting and the use of a complex regression equation may provide insights for linear and quadratic regressions in analytical and bioanalytical measurements.

• Journal of Digital Convergence
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• v.8 no.3
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• pp.19-37
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• 2010

One of the core issues in the realization of e-government is the effective implementation of a website. The current trend of e-government is developing individual web sites and portals, covering such fields as education, tax, economics, real estate, travel, and health. Evaluating e-government web sites is essential for improving web sites. These principles can be included in usability in a broader concept. Website usability has attracted considerable research on website evaluation and has been regarded as one of the most important criteria for measuring and evaluating websites. Usable e-government web sites make citizens willing to search for helpful information or solve their civil applications. The objective of this paper is to suggest an Analytic Hierarchy Process (AHP) method for evaluating e-government web sites. The proposed AHP method has two special characteristics compared to general AHP approaches. First, all citizens who are e-government users can evaluate both the usability criteria and the web sites, but the weighting mechanism differs between criteria and web sites. Secondly, a pairwise comparison is time-consuming and not cost effective with many criteria. Therefore for evaluating a website with respect to a sub-criterion, we develop checklist items as measure scales with a seven-point rating. This method is efficient as it enable us to avoid the pairwise comparison mechanism between sub-criteria. A new computation procedure for the AHP is developed that combines and synthesizes priorities of portals in the case that two decision maker groups are involved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.917-926
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• 2013

This study presents the feasibility of fuzzy multi-criteria decision making (MCDM) techniques for the robust prioritization of projects. It is applied to water resources planning problem. Results from weighted sum method (WSM), analytic hierarchy process (AHP), revised analytic hierarchy process (R-AHP), and TOPSIS are compared with those from Fuzzy WSM, Fuzzy, AHP, Fuzzy R-AHP, and Fuzzy TOPSIS. For the calculation, all weights on criteria and the normalized data were obtained from the same investigation. As a result, the rankings from four MCDM techniques are slightly different while those from fuzzy MCDM show the comparatively consistent ranking. Therefore, it is desirable to use fuzzy MCDM technique when MCDM is used for the prioritization problem, since fuzzy MCDM can include the uncertain variability of input data and weighting values on criteria.