• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2973-2978
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• 2011

In this paper, a system is developed to support multi-attribute decision making for designing light-weight of rolling stock. Conceptual design of light-weight of rolling stock does not only mean reducing weight. It should be considered about some attributes like safety and environment, technology, etc. So technical attributes and needs of customers, manufacturers and management companies, passengers, should be reflected and qualitative evaluation methods are required. AHP(Analytical Hierarchy Process) and QFD(Quality Function Deployment) are used to decide weighted values of technical attributes and needs from customers. Finally, Alternatives for light-weight of rolling stock that are composed of alternatives of equipment are evaluated by TOPSIS(Technique for Order Preference by Similarity to Ideal Solution). A series of this process are made as a S/W. It could suggest a near-optimal alternative for light-weight of rolling stock.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.210-214
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• 2002

Association rule mining is an exploratory learning task to discover some hidden dependency relationships among items in transaction data. Quantitative association rules denote association rules with both categorical and quantitative attributes. There have been several works on quantitative association rule mining such as the application of fuzzy techniques to quantitative association rule mining, the generalized association rule mining for quantitative association rules, and importance weight incorporation into association rule mining fer taking into account the users interest. This paper introduces a new method for generalized fuzzy quantitative association rule mining with importance weights. The method uses fuzzy concept hierarchies fer categorical attributes and generalization hierarchies of fuzzy linguistic terms fur quantitative attributes. It enables the users to flexibly perform the association rule mining by controlling the generalization levels for attributes and the importance weights f3r attributes.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.279-284
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• 2017

The visual impact of fonts on lots of documents and design work is significant. Accordingly, the users desire to appropriately use fonts suitable for their intention. However, existing font recommendation programs are difficult to consider what users want. Therefore, we propose a font recommendation system based on user-evaluated font attribute value. The properties of a font are called attributes. In this paper, we propose a font recommendation module that recommends a user 's desired font using the attributes of the font. In addition, we classify each attribute into three types of usage, personality, and shape, suggesting the font that is closest to the desired font, and suggest an optimal font recommendation algorithm. In addition, weights can be set for each use, personality, and shape category to increase the weight of each category, and when a weight is used, a more suitable font can be recommended to the user.

• Korean Journal of Agricultural Science
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• v.38 no.1
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• pp.183-190
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• 2011

The paper is to analyze multi-attributes for expanding new renewable energy in agricultural sectors which have environmental, technical, economic, and social factors consisting of 15 attributes which have both positive and negative impacts. We applied the analytic hierarchy process (AHP) to data from opinion polls. As a result of the AHP survey, the overall results indicate that the respondents more weight on economical factor than environmental, technical, and social factors for expanding new renewable energy. At the lowest level, a comparison of individual 15 attributes within three factors shows that fixed cost highest in multi-attributes, followed by operating cost, technical superiority. To achieve the public acceptance about expanding new renewable energy in agricultural sectors, the policy-makers should take all relevant factors into account through the decision-making process by the public opinions.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.3
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• pp.421-428
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• 2018

Objective: The aim of this study was to compare carcass traits, meat quality and sensory attributes in two different genotypes of geese according to age and sex. Methods: The experiment was carried out on 160 birds of two genotypes of geese: the Czech Goose (CG) breed and a Eskildsen Schwer (ES) hybrid. One-d-old goslings were divided into four groups according to genotype and sex. Two dates for slaughtering (at 8 and 16 wk of age of goslings) were undertaken. Results: The slaughter weight, cold carcass weight and dressing percentage were affected by all the studied factors, and significant interactions between age, genotype and sex were detected in the slaughter weight (p<0.001) and cold carcass weight (p = 0.004). The pH was not affected by any of studied factors, whereas in terms of meat colour parameters there were observed significant effects of age on $L^*$ and $b^*$ value and a significant effect of sex on $a^*$ value. The meat fat content was higher (p = 0.002) in ES. Higher score for overall acceptance of goose meat was recorded for ES at both ages compared to CG. Conclusion: ES had higher dressing percentage and better sensory attributes, whereas CG exceled in the favourable nutritional value of the meat.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.719-732
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• 2006

A set of clustering algorithms with proper weight on the formulation of distance which extend to mixed numeric and multiple binary values is presented. A simple matching and Jaccard coefficients are used to measure similarity between objects for multiple binary attributes. Similarities are converted to dissimilarities between i th and j th objects. The performance of clustering algorithms with balancing weight on different similarity measures is demonstrated. Our experiments show that clustering algorithms with application of proper weight give competitive recovery level when a set of data with mixed numeric and multiple binary attributes is clustered.

• IE interfaces
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• v.12 no.1
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• pp.43-48
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• 1999

This paper indicates deficiencies of existing weighting methods for decision problems that require trading off a selection of one alternative against others. Deficiencies originate from the definition of weight, $W_i$, satisfying that $W_i{\geq}0$ for all i and sums up to one and an assumption of independence between attributes. Thus, existing weighting methods can not handle a situation where all attributes are interrelated, resulting in that attributes can give either positive, or negative, contributions to the value of an alternative. In order to cope with deficiencies, this paper redefines weight and proposes a new causally related weighting method. The proposed method was applied in the study of developing a comprehensive organizational performance measurement system and showed a good performance.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.9-17
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• 1998

The evaluation structure of complex problems is composed of multi-attributes and hierarchy. A many studies were existed on this problems, but that based on the assumption that the evaluation elements were independent. The actual evaluation problems have the complexity, ambiguity and interlinkage among the elements. In this situation, the fuzzy evaluation process is very effective in settling the complex problems. For evaluation of large scale hierarchical MADM problem, the fuzzy evaluation algorithm is developed in this paper, and that is centering on the identification of fuzzy measures. In this study, we newly identified the weight and interaction among the evaluation attributes. The results of this study are as follows: we can identified the hierarchical structure of the evaluation problem which is composed of the evaluation structure, function and hierarchy; we improved the existed weighting method which could be accomplished by normalizing process, considering the uncertainty and new weight integrating method which come from Dempster-Shafer theory. And we take into account the interaction properties among more than 3 evaluation attributes, which can be compared with the existed studies in which only 2 evaluation attributes taked into account.

• Economic and Environmental Geology
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• v.41 no.5
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• pp.517-526
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• 2008

Geological and related thematic maps make various economical and social benefits at many sectors. Recently, development of information managing technology such as GIS, Geographic Information System, enlarges the usage of geological map and information. In this research, using the Analytic Hierarchy Process, we analyzed the weight of attributes which compose value of geological map and information. Results of research are as follows. By the analysis of the weight of attributes, we found that the weight of confidence, upper hierarchy attribute, was above 50%. The weight of convenience and additional effect was about $16%{\sim}30%$ in the geological map, geophysical map, geochemical map and hydrogeologic map. And the consumption of each maps will increase, especially in large scale map.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.75-84
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• 1994

The uncertainty in the relative weights of a pairwise comparison matrix n Multi-attribute Decision Making (MADM) is caused by imprecise preference information of decision maker. In this paper, it is shown how weight of attributes can be derived from the pairwise comparison matrix with interval pairwise comparison. The preference information of each pair of attributes with a point pairwise comparison is combined with an interval pairwise comparison in order to estimate a point pairwise comparison for a pair of attributes with the imprecise preference information. A numerical example shows the suggested procedure for deriving weights of attributes.