• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.1-11
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• 2016

Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.3
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• pp.79-88
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• 2011

In the context of sustainability which is understood as equilibrium among three elements; human, space and time, the imbalance within the Seoul metropolitan area hinders its own area or the nation from development. Claims for the balanced development in the area are set up on the premise that there is a locational order of priority among the zones named 'overpopulation suppression', 'growth management' and 'conservation'. Based on the systematic consideration of competitiveness this study adopts the premise as a research hypothesis. Factor scales derived from the factor analysis, a kind of multivariate dependence analysis play an important role in this research process since they are measured by interval-ratio level and can be used for dependent variables in the statistical analysis. The hypothesis test carried out by means of the analysis of variance(ANOVA) concludes that the hypothesis assuming no difference in the competitiveness is rejected but the alternative hypothesis of the locational order mentioned above should be adjusted. Eigenvalues derived from the factor analysis could be used as weights for aggregate factor scales and the scales show that the priority is in the order of growth management - overpopulation suppression - conservation zones. This finding has also a significant implication that the countermeasures to cope with the lowering of the competitiveness resulted from the continuous and absolute restraints should be provided. And strategic approaches which are composed of key factors for each zone are deducted from in-depth review. (1) overpopulation suppression zone; health-welfare, educational base, public service factors, focusing on health-welfare one, (2) growth management zone; public service factor and (3) conservation zone; health-welfare, educational base factors, also focusing on health-welfare one.