• Journal of Power System Engineering
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• v.18 no.1
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• pp.135-139
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• 2014

We propose some properties for fuzzy hypothesis test by fuzzy significance probability. First, we define fuzzy number data and fuzzy significance probability for repeatedly observed data with alternated error term. By the agreement index, we compare fuzzy significance probability with significance level and drawing conclusions the degree of acceptance and rejection by agreement index.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.19-24
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• 2009

We propose some properties for fuzzy binomial proportion test by agreement index. First we define fuzzy probability space and fuzzy type I error and type II error for the fuzzy probability of the two type errors. Also, we show that a fuzzy power function of performance for a fuzzy hypothesis test and drawing conclusions from the test.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.46-49
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• 2002

We propose some properties of hybrid number the addition of fuzzy number and random variable and test the fuzzy hypotheses by agreement index for the hybrid number.

• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.126-132
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• 2005

The purpose of this study is to propose a method to evaluate task complexity using CIFs(Complexity Influencing Factors). We developed a method that CIFs can be used in the evaluation of task complexity using fuzzy linguistic approach. That is, a fuzzy linguistic multi-criteria method to assess task complexity in a specific task situation was proposed. The CIFs luting was assessed in linguistic terms, which are described by fuzzy numbers with triangular and trapezoidal membership function. A fuzzy weighted average algorithm, based on the extension principle, was employed to aggregate these fuzzy numbers. Finally, the method was validated by experimental approach. In the result, it was validated that TCIM(Tink Complexity Index Method) is an efficient method to evaluate task complexity because the correlation coefficient between task performance time and TCI(Task Complexity Index) was 0.699.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.1-5
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• 2011

We furnished some properties of fuzzy testing of independence for correlation in a bivariate normal distribution by agreement index. First we present some restriction of the fuzzy data, define fuzzy sample correlation coefficient and agreement index for testing hypothesis with acceptance or rejection degree. Also, we show that UMP unbiased fuzzy test and drawing conclusions the fuzzy test.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.614-618
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• 2007

We propose some properties of fuzzy p-value and fuzzy significance level to the fuzzy hypotheses testing for vague response data with reflected correlation in survey research, Appling the principle of agreement index, we suggest the methods for fuzzy hypothesis testing by fuzzy rejection region.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.25-28
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• 2011

In this paper, we study some properties of condition for fuzzy data, agrement index by ratio of area and the uniformly most powerful fuzzy test of hypothesis. Also, we suggest a confidence bound for uniformly most powerful fuzzy test. For illustration, we take the most powerful critical fuzzy region from exponential distribution by likelihood ratio and test the hypothesis of ${\chi}^2$-distribution by agreement index.

• IE interfaces
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• v.9 no.1
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• pp.53-62
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• 1996

The Delphi method is widely used for long and middle range forecasting in management science. It is a method by which the subjective data of experts are made to converge using statistical analysis. The Fuzzy Delphi Method(F.D.M.), anew application of the Delphi method using Triangular Fuzzy Numbers(T.F.N.), can help to predict the uncertainty, synthesize the opinion and calculation of those assumed dissemblance index and fuzzy distance. Furthermore, the programming of the F.D.M. process to feed paper and data back to experts can make them more accurately predict the various information.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.281-285
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• 2002

The observation fuzzy data in random effect and balanced designs for one way classification by using a the matrix formulation, we can estimate the fuzzy variance components for the ozone depletion example and test by the agreement index.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.455-460
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• 2003

A new cluster validity index is proposed that determines the optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index exploits an overlap measure and a separation measure between clusters. The overlap measure is obtained by computing an inter-cluster overlap. The separation measure is obtained by computing a distance between fuzzy clusters. A good fuzzy partition is expected to have a low degree of overlap and a larger separation distance. Testing of the proposed index and nine previously formulated indexes on well-known data sets showed the superior effectiveness and reliability of the proposed index in comparison to other indexes.