• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.304-308
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• 2014

Accurate prediction of peak bloom dates (PBD) of flowering cherry trees is critical for organizing local cherry festivals and other associated cultural and economic activities. A two-step phenology model is commonly used for predicting flowering time depending on local temperatures as a result of two consecutive steps followed by chill and heat accumulations. However, an extensive computation requirement for parameter estimation has been a limitation for its practical use. We propose a sequential parameterization method by exploiting previously unused records of development stages. With an extra constraint formed by heat accumulation between two intervening stages, each parameter can then be solved sequentially in much shorter time than the brute-force method. The result was found to be almost identical to the previous solution known for cherry trees (Prunus ${\times}$ yedoensis) in the Tidal Basin, Washington D.C.

• Asia Marketing Journal
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• v.6 no.2
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• pp.55-68
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• 2004

After Nakanishi and Cooper(1982) suggested a way of transforming the complicated nonlinear MCI model into a simple linear form, the application of MCI model has been increased. However, the use of MCI model in Korea is quite limited. The goal of this paper is to demonstrate the practical application of MCI(Multiplicative Competitive Interaction) model to a consumer goods industry. MCI model is a form of the attraction model explaining the relation between marketing mix variables and market share. In this study, multiple sources of empirical data are incorporated in the model formulation stage. In the estimation process, the equity estimation is applied to solve the possible multi-collinearity problem among marketing mix variables. Results from the fitted model suggest meaningful managerial implications for the management of brand equity and the allocation of resources among marketing mix variables.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2002.05a
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• pp.3-8
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• 2002

대규모 수험자를 대상으로 하는 경우, CBT 방식은 PBT 방식에 비해 비용이나 처리 방법에 있어 효율적이라는 장점을 갖고 있다. 하지만, CBT 평가가 제대로 운영되려면 많은 문항으로 구성된 대규모의 문제 은행이 있어야 하며, 기 구축된 문항은 적합성과 공정성이 반드시 보장되어야 한다. 이에 본 연구는 4,000여 명 이상의 수험자를 대상으로 8000문제가 넘는 문제 은행이 구축되어 실제 CBT 시스템을 개발·운영하고 있는 P 대학교 CBLT 테스트 시스템의 문항들을 분석할 방법을 제안한다. 연구 결과 CBLT 테스트 시스템의 문제 은행의 개별 문항들이 출제자 1인의 주관적 판단에 달려있어 문항에 대한 질 관리가 어렵다는 문제점을 해결하기 위해서는 고전검사이론이 적합하다고 판단된다. 그러나 매 시험이 동질한 문항 세트로 구성되기 위해서는 문항에 대한 충분하고 객관적인 자료가 절대적으로 필요하다. 이를 위해서는 CBLT 테스트 시스템과 같이 응답자 수가 2∼300여 명 전후이며, 40문항의 문항 세트에 대한 분석은 2모수 정도가 적당하다고 판단된다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.423-429
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• 2014

This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.161-161
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• 2017

본 연구는 효율적인 매개변수 추정 방법인 Isolated-Speciation Particle Swarm Optimization(ISPSO)와 불확실도 분석 기법인 GLUE를 결합한 ISPSO-GLUE의 개념을 도입하였다. 임의 매개변수 추출을 방식인 GLUE 기법과 ISPSO-GLUE와의 효율성 비교를 위해 분포형 강우-유출모형인 TOPMODEL에 적용하였으며, 추정된 매개변수에 대한 모의 유량치를 이용하여 성능을 비교하였다. 연구대상지는 Texas의 $1000{\times}2000km^2$ 크기 내외의 두 유역을 택하였으며, 2002-2007년을 보정기간으로 하고, 2008-2013년을 검증기간으로 설정하였다. 불확실도 분석에 10개의 TOPMODEL 매개변수를 이용하고, 우도함수로는 Nash-Sutcliffe(NS) Coefficient이용하여 0.6이상 기준으로 행동모형을 구분하였다. 분석 결과 모수 추정성능면에서, 누적 최대 NS 값과 행동 모형의 개수는 전반적으로 ISPSO-GLUE에서 큰 값을 보였으나, 불확실도 구간에 속하는 관측치는 GLUE에서 더 높은 경향을 보였다. 이는 ISPSO-GLUE의 편향된 모수 추정으로 불확실도 구간이 작아지며, 포함되는 관측치가 GLUE에 비하여 적게 되는 것으로 확인되었다. ISPSO-GLUE의 개선을 통하여 TOPMODEL에 대한 적용성을 증진시키고, 값비싼 수문모형에 대한 매개변수 추정에 더 큰 효과를 가져올 것으로 기대된다.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1001-1019
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• 2017

The signal processing is a field of the electrical engineering but it is very much related with the time series analysis. Thesedays the commercial softwares are widely used by the reseachers. We have attempted to make a guide for using the R-package in the digital signal processing. It would be good to read the materials in each section first and to follow the plots in the section 8 and to run the attached R-codes. The article consists of (1) Fourier transform and Fourier inverse transform, (2) spectral analysis (3) parametric and non-parametric estimation for the period (4) filter design. Simple theoretical explanations are provided and R implementations are added.

• The Journal of Society for e-Business Studies
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• v.22 no.1
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• pp.15-35
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• 2017

The method of weighted sum of evaluation using AHP is widely used in feasibility analysis and alternative selection. Final scores are given in forms of weighted sums and the alternative with largest score is selected. With two alternatives, as in feasibility analysis, the final score greater than 0.5 gives the selection but there remains a question that how large is large enough. KDI suggested a concept of 'grey area' where scores are between 0.45 and 0.55 in which decisions are to be made with caution, but it lacks theoretical background. Statistical testing was introduced to answer the question in some studies. It was assumed some kinds of probability distribution, but did not give the validity on them. We examine the various cases of weighted sum of evaluation score and show why the statistical testing has to be introduced. We suggest a non-parametric testing procedure which does not assume a specific distribution. A case study is conducted to analyze the validity of our suggested testing procedure. We conclude our study with remarks on the implication of analysis and the future way of research development.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.437-465
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• 2019

In this study, we propose a new method to forecast long-term energy demand in Korea. Based on Chang et al. (2016), which models the time varying long-run relationship between electricity demand and GDP with a function coefficient panel model, we design several schemes to retain objectivity of the forecasting model. First, we select the bandwidth parameters for the income coefficient based on the out-of-sample forecasting performance. Second, we extend the income coefficient using the functional principal component analysis method. Third, we proposed a method to reflect the elasticity change patterns inherent in Korea. In the empirical analysis part, we forecasts the long-term energy demand in Korea using the proposed method to show that the proposed method generates more stable long term forecasts than the existing methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.429-430
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• 2019

본 논문에서는 최적화 기법에 기반한 지능형 시스템의 재무응용사례를 다룬다. 본 연구에서 제안하는 모형은 대표적인 최적화 기법 중 하나인 시뮬레이티드 어니일링인데 이는 유전자 알고리듬과 유사한 최적화 성능을 가지고 있는 것으로 알려져 있으나 재무분야에서 응용된 사례가 거의 없다. 본 연구에서 제안하는 지능형 시스템은 시뮬레이티드 어니일링과 기계학습 기법을 결합한 것이다. 일반적으로 최적화와 기계학습 기법을 결합하는 방법은 특징선택(feature selection), 특징 가중치 최적화(feature weighting), 사례선택(instance selection), 모수 최적화(parameter optimization) 등의 방법이 있는데 선행연구에서 가장 많이 사용된 것은 특징선택에 두 기법을 결합하는 방식이다. 본 연구에서도 기계학습 기법을 재무 문제에 활용함에 있어서 최적의 특징선택을 위해 시뮬레이티드 어니일링을 결합하는 방식을 사용한다. 본 연구에서 제안된 기법의 유용성을 확인하기 위하여 실제 재무분야의 데이터를 활용하여 예측 정확도를 확인하였으며 그 결과를 통하여 제안하는 모형의 유용성을 확인할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.21 no.7
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• pp.641-647
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• 2002

In this paper, we propose the reduction method of the number of parameters in the segmental-feature HMM using trend quantization method. The proposed method shares the trend information of the polynomial trajectories by quantization. The trajectory is obtained by the sequence of feature vectors of speech signals and can be divided by trend and location information. The trend indicates the variation of consequent frame features, while the location points to the positional difference of the trajectories. Since the trend occupies the large portion of SFHMM, if the trend is shared, the number of parameters maybe decreases. To exploit the proposed system the experiments are performed on TIMIT corpus. The experimental results show that the performance of the proposed system is roughly similar to that of previous system. Therefore, the proposed system can be considered one of parameter reduction method.