• Journal of the Korean Mathematical Society
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• v.16 no.2
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• pp.161-166
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• 1980

• Journal of the Korean Mathematical Society
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• v.18 no.1
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• pp.37-42
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• 1981

• Journal of the Korean Mathematical Society
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• v.14 no.2
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• pp.229-234
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• 1978

• Kyungpook Mathematical Journal
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• v.18 no.2
• /
• pp.151-157
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• 1978

• Kyungpook Mathematical Journal
• /
• v.17 no.2
• /
• pp.171-173
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• 1977

• Kyungpook Mathematical Journal
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• v.28 no.1
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• pp.71-77
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• 1988

• Journal of the Korean Mathematical Society
• /
• v.8 no.2
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• pp.69-72
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• 1971

• Journal of the Chungcheong Mathematical Society
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• v.25 no.3
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• pp.501-505
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• 2012

In this paper, general classes of continuous distributions are characterized by considering the conditional expectations of functions of upper record statistics. The specific distribution considered as a particular case of the general class of distribution are Exponential, Exponential Power(EP), Inverse Weibull, Beta Gumbel, Modified Weibull(MW), Weibull, Pareto, Power, Singh-Maddala, Gumbel, Rayleigh, Gompertz, Extream value 1, Beta of the first kind, Beta of the second kind and Lomax.

• Bulletin of the Korean Mathematical Society
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• v.36 no.4
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• pp.723-736
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• 1999

The paper is devoted to generalizations of continuity of set-valued mappings and some properties of hypertopologies on the collection of some subsets of a topological space. It is also dedicated to continuous selection theorems without relatively higher separation axioms. More precisely, we give characterizations of $\lambda$-collectionwise normality using continuous functions as in Michael's papers.

• Industrial Engineering and Management Systems
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• v.15 no.2
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• pp.148-155
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• 2016

Existing power plants may consume significant amounts of fuel and require high operating costs, partly because of poor electrical power output estimates. This paper suggests a continuous conditional random field (C-CRF) model to predict more precisely the full-load electrical power output of a base load operated combined cycle power plant. We introduce three feature functions to model association potential and one feature function to model interaction potential. Together, these functions compose the C-CRF model, and the model is transformed into a multivariate Gaussian distribution with which the operation parameters can be modeled more efficiently. The performance of our model in estimating power output was evaluated by means of a real dataset and our model outperformed existing methods. Moreover, our model can be used to estimate confidence intervals of the predicted output and calculate several probabilities.