• Journal of the Korean Data and Information Science Society
• /
• v.15 no.3
• /
• pp.617-624
• /
• 2004

In this article the fuzzy number rank and the fuzzy rank transformation method are introduced in order to analyse the non-parametric fuzzy regression model which cannot be described as a specific functional form such as the crisp data and fuzzy data as a independent and dependent variables respectively. The effectiveness of fuzzy rank transformation methods is compared with other methods through the numerical examples.

• Journal of Korean Society for Quality Management
• /
• v.41 no.4
• /
• pp.709-724
• /
• 2013

Purpose: The purpose of this study is to examine five evaluation models constructed by different normalization and aggregation methods in terms of the volatility of rankings and rank reversals. We also explore how the volatility of rankings of the five models changes and how often the rank reversals occur when the outliers are removed. Methods: We used data published in the Complete University Guide 2014. Two universities with missing values were excluded from the data. The university rankings were derived by using the five models, and then each model's volatility of rankings was measured. The box-plot was used to detect outliers. Results: Model 1 has the lowest volatility among the five models whether or not the outliers are included. Model 5 has the lowest number of rank reversals. Model 3, which has been used by many institutions, appears to be in the middle among the five in terms of the volatility and the rank reversals. Conclusion: The university rankings vary from one evaluation model to another depending on what normalization and aggregation methods are used. No single model exhibits clear superiority over others in both the volatility and the rank reversal. The findings of this study are expected to provide a stepping stone toward a superior model which is both reliable and robust.

• Communications for Statistical Applications and Methods
• /
• v.10 no.3
• /
• pp.1007-1015
• /
• 2003

In this paper we introduced a new score generating function for the rank dispersion function in a general linear model. Based on the new score function, we derived the null asymptotic theory of the rank-based hypothesis testing in a linear model. In essence we showed that several rank test statistics, which are primarily focused on our new score generating function and new dispersion function, are mainly distribution free and asymptotically converges to a chi-square distribution.

• Transactions of the Korean hydrogen and new energy society
• /
• v.30 no.2
• /
• pp.178-187
• /
• 2019

Due to the increasing demand of high rank coal, the use of low rank coal, which has economically advantage, is rising in various industries using carbonaceous solid fuels. In addition, the severe disaster of global warming caused by greenhouse gas emissions is becoming more serious. The Republic of Korea set a goal to reduce greenhouse gas emissions by supporting the use of biomass from the Paris International Climate Change Conference and the 8th Basic Plan for Electricity Supply and Demand. In line with these worldwide trends, this paper focuses on investigating the combustibility of high rank coal Carboone, low rank coal Adaro from Indonesia, Baganuur from Mongolia and, In biomass, wood pellet and herbaceous type Kenaf were simulated as kinetic reactivity model. The accuracy of the pore development model were compared with experimental result and analyzed using carbon conversion and tau with grain model, random pore model, and flexibility-enhanced random pore model. In row lank coal and biomass, FERPM is well-matched kinetic model than GM and RPM to using numerical simulations.

• Journal of the Chungcheong Mathematical Society
• /
• v.26 no.1
• /
• pp.181-190
• /
• 2013

In this paper we study the Putinar's matricial model operator of rank 2 and provide some evidences for the validity of the conjecture in [8].

• The Journal of the Korea Contents Association
• /
• v.17 no.1
• /
• pp.201-212
• /
• 2017

This study presented the new evaluation index which can evaluate the discrimination of DEA models. To evaluate the discrimination of DEA models, data were analyzed using importance index as suggested in previous study and the coefficient of variation as suggested in this study for the discrimination evaluation. This study selected the CCR-DEA, BCC-DEA, entropy, bootstrap, super efficiency, and cross efficiency DEA model for the discrimination evaluation and accomplished empirical analysis. In order to grasp the rank correlation of the models, this study implemented the rank correlation analysis between the efficiency of CCR model and BCC model and entropy, bootstrap, super efficiency, and efficiency of the cross efficiency model. The obtained results of this study are as follows. First, the discrimination rank of models using the importance index and the coefficient of variation was shown to be identical. Therefore, the coefficient of variation can be used the discrimination evaluation index of DEA model. Second, the discrimination of the super efficiency model was found to be the highest rank among 4 models according to the analysis of this present study. Third, the highest rank correlation with CCR model was the super efficiency model. In addition, the super efficiency model was found to be the highest rank correlation with BCC model.

• Transactions of the Korean hydrogen and new energy society
• /
• v.26 no.6
• /
• pp.567-580
• /
• 2015

In order to select an optimum gasifier for specific low rank coal, evaluation elements were studied by analyzing characteristics of low rank coal compared with those of high rank coal and the effects of each gasifier type in accordance with the characteristics. And syngas composition calculation model was made on the basis of thermochemical equilibrium to quantify some of the evaluation elements. And then the suitable gasifier was selected for a kind of Indonesian low rank coal through this syngas composition calculation model and the evaluation elements of selecting gasifier.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.2
• /
• pp.333-339
• /
• 2013

This paper discusses a method for getting a basis set of estimable functions of less than full rank linear model. Since model parameters are not estimable estimable functions should be identified for making inferences proper about them. So, it suggests a method of using full rank factorization of model matrix to find estimable functions in easy way. Although they might be obtained in many different ways of using model matrix, the suggested full rank factorization technique could be one of much easier methods. It also discusses how to use projection matrix to identify estimable functions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.15 no.11
• /
• pp.955-961
• /
• 1990

Test statistics are obtained for detection of weak signals in signal-dependent noise using rank statistics. A generalized model is used in this paper in order to consider non-additivenoise as well as purely-additive noise. Locally optimum rank detectors for the model are shown to have similarity to locally optimum detectors and to be generalizations of these for the purely-additive noise model. A similar result is obtained for multi-input cases.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.1
• /
• pp.79-85
• /
• 1996

This paper will show that the rank of the model matrix of a closed, n compartmental model with k sinks is n-k. This statement will be extended to include open compartmental models as a part of theorem.