• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 춘계학술대회 학술발표 논문집
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• pp.29-33
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• 2001

We propose fuzzy least-squares regression analysis by few error term data and test the slop by fuzzy hypotheses membership function for fuzzy number data with agreement index. Finding the agreement index by area for fuzzy hypotheses membership function and membership function of confidence interval, we obtain the results to acceptance or reject for the test of fuzzy hypotheses.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.363-366
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• 2004

We propose some properties of fuzzy multonomial analysis of variance by fuzzy vector operation with agreement index.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권1호
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• pp.97-100
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• 2004

We propose some properties of fuzzy multivariate analysis of variance by fuzzy vector operation with agreement index. We deals fuzzy null hypotheses and fuzzy alternative hypothesis and define the agreement index for the grades of the judgements that the hypothesis is rejection or acceptance. Finally, we provide an example to evaluate the judgements.

• 한국수자원학회논문집
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• 제44권11호
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• pp.903-913
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• 2011

본 논문에서는 상수관로의 개량(교체또는갱생) 우선순위를 결정하는데 있어서 평가되어야 할 인자 또는 요소를 관로의 파손이 전체관망에 미치는 영향 및 개별관로의 특성으로 구분하였고, 이들을 퍼지기법을 적용하여 정량적으로 산정할 수 있는 모형을 개발하였다. 퍼지기법으로 산정되는 관로의 파손이 전체관망에 미치는 영향을 관로의 퍼지 중요도로 정의하였으며, 개별관로의 특성은 관로의 퍼지 특성도로 정의하였다. 퍼지 특성도는 다시 퍼지 노후도 및 퍼지 난이도 등으로 구분하여 산정할 수 있게 하였다. 한편, 각 평가요소를 퍼지기법으로 산정함에 있어서 적합한 평가대상이 차지하는 비중에 따라 평가대상의 가중치를 고려할 수 있도록 하였다. 본 연구에서 개발된 방법론의 적용예를 제시하기 위하여 EPANET 관망해석 프로그램의 예제관망으로 제공되는 Net3 관망을 이용하였다. 관로의 파손이 전체관망에 미치는 수리학적 영향과 개별 관로의 특성중의 하나인 관로의 노후도를 Net3 관망내 관로 개량 우선순위 결정에 고려하여야 할 요소로 선정하여 Net3 관망 내 관로의 퍼지 중요도(Fuzzy Importance Index, FII) 및 퍼지 노후도(Fuzzy Deterioration Index, FDI)를 산정하였으며, 이를 이용하여 Net3 관망내 관로의 개량 우선순위를 수립하였다.

• Communications for Statistical Applications and Methods
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• 제19권1호
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• pp.147-155
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• 2012

We propose some properties for a fuzzy correlation test by reduced-spread fuzzy variance for sample fuzzy data. First, we define the condition of fuzzy data for repeatedly observed data or that which includes error term data. By using the average of spreads for fuzzy numbers, we reduce the spread of fuzzy variance and define the agreement index for the degree of acceptance and rejection. Given a non-normal random fuzzy sample, we have bivariate normal distribution by apply Box-Cox power fuzzy transformation and test the fuzzy correlation for independence between the variables provided by the agreement index.

• 산업경영시스템학회지
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• 제15권26호
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• pp.111-117
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• 1992

In the stock marketing. investor needs speedy and accurate decision making for the investment. A stock exchange index provides the important index of the early of 1993 in Korea using Fuzzy Delphi Method(F. D. M) which is widely used to a mid and long range forecasting in decision making problem. In the Fuzzy Delphi method, considerably qualified experts an first requested to give their opinion seperately and without intercommunication. The forecasting data of experts consist of Triangular Fuzzy Number (T.F.N) which represents the pessimistic, moderate, and optimistic forecast of a stock exchange index. A statistical analysis and dissemblance index are then made of these subject data. These new information are then transmitted to the experts once again, and the process of reestimation is continued until the process converges to a reasonable stable forecast of stock exchange index. The goal of this research is to forecast the stock exchange index using F.D.M. in which subjective data of experts are transformed into quasi -objective data index by some statistical analysis and fuzzy operations. (a) A long range forecasting problem must be considered as an uncertain but not random problem. The direct use of fuzzy numbers and fuzzy methods seems to be more compatible and well suited. (b) The experts use their individual competency and subjectivity and this is the very reason why we propose the use of fuzzy concepts. (c) If you ask an expert the following question: Consider the forecasting of the price index of stocks in the near future. This experts wi11 certainly be more comfortable giving an answer to this question using three types of values: the maximum value, the proper value, and the minimum value rather than an answer in terms of the probability.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2006년도 춘계학술대회 학술발표 논문집 제16권 제1호
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• pp.199-202
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• 2006

We propose some properties of fuzzy p-value and fuzzy significance level to the test statistics for the fuzzy hypotheses testing. Appling the principle of agreement index, we suggest two method for fuzzy hypothesis testing by fuzzy rejection region and fuzzy p-value with fuzzy hypothesis $H_{f,0}$.

• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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• pp.33-36
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• 2008

We introduce some properties for fuzzy binomial distributions with fuzzy valued probability. First we define fuzzy type I error and type II error for fuzzy relative frequency and agreement index. And we show that an fuzzy power function and fuzzy binomial frequency function for binomial proportion test.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권3호
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• pp.170-174
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• 2008

The measurement of performance of a process considering both the location and the dispersion of information about the process is referred to as the process capacity indices (PCIs) of interest, $C_{pk}$. This information is presented by the mean and standard deviation of the producing process. Linguistic variables are used to express the evaluation of the quality of a product. Consequently, $C_{pk}$ is defined with fuzzy numbers. Lee [Eur. J. Oper. Res. 129(2001) 683-688] constructed the definition of the $C_{pk}$ index estimation presented by fuzzy numbers and approximated its membership function using the "min" - norm based Zadeh's extension principle of fuzzy sets. However, Lee's result was shown to be invalid by Hong [Eur. J. Oper. Res. 158(2004) 529-532]. It is well known that $T_w$ (the weakest t-norm)-based addition and multiplication preserve the shape of L-R fuzzy numbers. In this paper, we allow that the fuzzy numbers are of L-R type. The object of the present study is to propose a new method to calculate the $C_{pk}$ index under $T_w-based$ fuzzy arithmetic operations.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.20-21
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• 2002

Recently, Lee[European J. Operational Research 129(2001) 682-688] calculated standard deviation of fuzzy numbers in order to obtain the membership function of the process capacity index (PCI) $C^{pk}$. In this note, we show that his result is not valid.