• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2001.11a
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• pp.111-116
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• 2001

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.73-82
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• 2013

In pattern classification, feature selection is an important factor in the performance of classifiers. In particular, when classifying a large number of features or variables, the accuracy and computational time of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. The proposed method consists of two parts: a wrapper part with an improved genetic algorithm(GA) using a new reproduction method and a filter part using mutual information. We also considered feature selection methods based on mutual information(MI) to improve computational complexity. Experimental results show that this method can achieve better performance in pattern recognition problems than other conventional solutions.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.6
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• pp.567-570
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• 1997

A multiple trait animal model having milk yield and lactation length was used to estimate genetic parameters using data from four institutional herds and four field recording centers. Response to selection for milk yield alone and in combination with lactation length was estimated by using principles of genetic theory. Lactation records (n = 2,353) adjusted for age at calving to 60 months were utilized. Milk yield was 17% heritable with repeatability of 0.44. Lactation length had a low heritability of 0.06 with repeatability of 0.16. Genetic correlation between the two traits was 0.70. Selection response in milk yield can be improved slightly (103.8 vs 102.8 kg) when information on covariance with lactation length is used together with the information on milk yield.

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.108-111
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• 2007

속성선택(Feature Selection)은 패턴분류 문제에서 분류기들의 성능을 향상시킬 수 있는 중요한 부분으로 다양한 기법들이 연구되어지고 있다. 특히, 많은 변수와 속성들을 가지는 데이터를 패턴분류 하는 과정에서 주요 속성부분집합을 추출하여 이용함으로써 분류기의 연산속도 및 정확도를 향상시킬 수 있다. 본 논문에서는 유전자 알고리즘과 정보이론의 상호정보량을 이용하여 속성선택을 하는 기법을 제안하였다. 제안된 기법의 성능을 평가하기 위하여 패턴분류 문제에 적용하고 그 성능이 우수함을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1553-1556
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• 1991

This paper deals with a problem on the selection of alternative tools in a flexible manufacturing system (FMS) where a lot of tools are required to produce a large variety of product items. An approach using branch and bound method is proposed to minimize a total number of tools required through the optimal use of the alternative tools. In this approach, tools are initially divided into tool subgroups based on graph theory for the purpose of the effective search of the optimal solution. A small example is also presented to highlight the effectiveness of the proposed approach.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.85-93
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• 2005

Tweedie (1957a) proposed a method for the analysis of residuals from an inverse Gaussian population paralleling the analysis of variance in normal theory. He called it the analysis of reciprocals. In this paper, we propose a Bayesian model selection procedure based on the fractional Bayes factor for the analysis of reciprocals. Using the proposed model procedures, we compare with the classical tests.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.377-386
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• 2004

A technique that provides prediction intervals based on a model called an empirical linear model is discussed. The technique, high-dimensional empirical linear prediction (HELP), involves principal component analysis, factor analysis and model selection. HELP can be viewed as a technique that provides prediction (and confidence) intervals based on a factor analysis models do not typically have justifiable theory due to nonidentifiability, we show that the intervals are justifiable asymptotically.

• Journal of the Korean Home Economics Association
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• v.36 no.11
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• pp.209-218
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• 1998

The purpose of this study was to conduct the review of female labor suply, and thus, to provide useful theoretical and empirical frameworks for future studies related to female labor supply. Based on the theory of the allocation of time, the process of individual labor supply was systematically reviewed. Participation Probit/Logit, Tobit, and Selection B;ias Corrected Regression were considered in estimating the function of female labor supply which modifies the selection bias. Based on the previous empirical results, wage rate, asset income, husband's income, the level of eduction, and child-related variables such as the presence of child and the number of children might be considered for the empirical specification of female labor supply.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.745-750
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• 2008

In a cognitive radio based system, quality of service (QoS) for the secondary user must be maintained as much as possible even while that of the primary user is protected all he time. In particular, switching wireless links for the secondary user during the transmission of multimedia data causes delay and information loss, and QoS degradations occur inevitably. The efficient resource management scheme is necessary to support the seamless multimedia service to the secondary user. This paper proposes a novel frequency selection method based on Multi-Criteria Decision Making (MCDM), in which uncertain parameters such as received signal strength, cell load, data rate, and available bandwidth are considered during the decision process for the frequency selection with the fuzzy set theory. Through simulation, we show that our proposed frequency selection method provides a better performance than the conventional methods which consider the received signal strength only.