• 대한수학회보
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• 제38권3호
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• pp.463-474
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• 2001

We find Rodrigues type formula for multi-variate orthogonal polynomial solutions of second order partial differential equations.

• Journal of the Korean Data and Information Science Society
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• 제14권1호
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• pp.131-141
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• 2003

In this paper, we prove that multi-variate fuzzy polynomials are universal approximators for multi-variate fuzzy functions which are the extension principle of continuous real-valued function under $T_W-based$ fuzzy arithmetic operations for a distance measure that Buckley et al.(1999) used. We also consider a class of fuzzy polynomial regression model. A mixed non-linear programming approach is used to derive the satisfying solution.

• 전기학회논문지
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• 제66권3호
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• pp.493-499
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• 2017

This paper proposes a combined very-short-term and short-term multi-variate time-series model for 24 hour load forecasting. First, the best model for very-short-term and short-term load forecasting is selected by considering the least error value, and then they are combined by the optimal forecasting time. The actual load data of industry complex is used to show the effectiveness of the proposed model. As a result the load forecasting accuracy of the combined model has increased more than a single model for 24 hour load forecasting.

• 대한원격탐사학회지
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• 제22권6호
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• pp.581-593
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• 2006

다양한 지질 주제도는 현지 조사에 의해 부분적으로 샘플링된 공간 자료의 내삽을 통해 작성되어 왔으며, 공간적 예측을 위해 공간적 상관성을 고려하는 지구통계학적 크리깅이 많이 적용되어 왔다. 이 논문에서는 지질 주제도 작성을 목적으로 부분적인 샘플링 자료와 이와 상관된 부가자료를 통합하기 위해 다변량 지구통계 기법을 적용하였다. 다변량 지구통계 기법으로 simple kriging with local means와 kriging with an external drift를 적용하였다. 지하수위 분포도 작성과 퇴적물 입도 분포도 작성의 2가지 사례연구를 수행하였는데, 지하수위 분포도 작성에는 지하수위 분포 샘플링 자료와 수치고도모델을, 퇴적물 입도분포도 작성에는 입도 샘플링 자료와 IKONOS 원격탐사 자료를 이용하였다. 사례연구 수행결과, 다변량 지구통계 기법이 그동안 많이 이용되어온 단변량 지구통계 기법 친 정규 크리깅에 비해 작은 추정 오차를 나타내면서 국소적인 특성을 반영할 수 있었다. 그러나 추정 오차의 정도는 샘플링 밀도, 부가자료와의 상관성과 공간자료 자체의 상관성 정도에 영향을 받는 것으로 나타났는데, 특히 퇴적물 입도 분포도 작성 사례연구에서 이러한 요소들이 상호 영향을 미쳐 부가자료의 이용 효과가 상대적으로 적게 나타났다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1990년도 봄 학술발표회 논문집
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• pp.24-30
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• 1990

An improved algorithm for simulation of multi-variate random processes has been presented. It is based on the spectral representation method. The conventional methods give sample time histories which satisfy the target spectral density matrix only in the sense of ensemble average. However, the present method can generate sample functions which satisfy the target spectra in the ergodic sense. Example analysis is given for the simulation of earthquake accelerations with three components.

• 산업공학
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• 제24권2호
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• pp.97-104
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• 2011

Research for multi-variate classification has been studied through two kinds of procedures which are feature selection and classification. Feature Selection techniques have been applied to select important features and the other one has improved classification performances through classifier applications. In general, each technique has been independently studied, however consideration of the interaction between both procedures has not been widely explored which leads to a degraded performance. In this paper, through integrating these two procedures, classification performance can be improved. The proposed model takes advantage of KBANN (Knowledge-Based Artificial Neural Network) which uses prior knowledge to learn NN (Neural Network) as training information. Each NN learns characteristics of the Feature Selection and Classification techniques as training sets. The integrated NN can be learned again to modify features appropriately and enhance classification performance. This innovative technique is called ALBNN (Algorithm Learning-Based Neural Network). The experiments' results show improved performance in various classification problems.

• Wind and Structures
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• 제1권2호
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• pp.161-174
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• 1998

Wind forces on structures are usually schematized by the sum of their mean static part and a nil mean fluctuation generally treated as a stationary process randomly varying in space and time. The multi-variate and multi-dimensional nature of such a process requires a considerable quantity of numerical procedures to carry out the dynamic analysis of the structural response. With the aim of drastically reducing the above computational burden, this paper introduces a method by means of which the external fluctuating wind forces on slender structures and structural elements are schematized by an equivalent process identically coherent in space. This process is identified by a power spectral density function, called the Generalized Equivalent Spectrum, whose expression is given in closed form.

• 아동학회지
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• 제28권5호
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• pp.253-267
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• 2007

This study examined the relationships between multiple intelligences as cognitive factors and affective factors of learning motivation and academic self-concept. The data were collected from 276 4th grade elementary school students and analyzed by correlation, multi-variate analysis, and step-wise multiple regression. Results were that (1) multiple intelligences, learning motivation, and academic self-concept had statistically significant correlations among themselves. Multi-variate analysis showed that intra-personal intelligence explained 58.6% of the linear combination of learning motivation and academic self-concept. (2) Intra-personal intelligence explained 29% to 58% of learning motivation and its sub-factors of achievement motivation, internal locus of control, self-efficacy, and self-regulation. (3) Intra-personal intelligence, logical-mathematical intelligence, musical intelligence, and inter-personal intelligence were explanatory variables for academic self-concept and its sub-factors.

• Wind and Structures
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• 제3권4호
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• pp.221-241
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• 2000

Structural dynamics usually applies modal transformation rules aimed at de-coupling and/or minimizing the equations of motion. Proper orthogonal decomposition provides mathematical and conceptual tools to define suitable transformed spaces where a multi-variate and/or multi-dimensional random process is represented as a linear combination of one-variate and one-dimensional uncorrelated processes. Double modal transformation is the joint application of modal analysis and proper orthogonal decomposition applied to the loading process. By adopting this method the structural response is expressed as a double series expansion in which structural and loading mode contributions are superimposed. The simultaneous use of the structural modal truncation, the loading modal truncation and the cross-modal orthogonality property leads to efficient solutions that take into account only a few structural and loading modes. In addition the physical mechanisms of the dynamic response are clarified and interpreted.

• 대한조선학회논문집
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• 제39권2호
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• pp.69-80
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• 2002

선박의 곡외판은 냉간가공과 열간가공(선상가열) 과정을 거쳐 제작된다. 선상가열의 자동화 및 기계화에 대한 연구가 다양하게 수행되어 오고 있다. 특히 가열조건과 잔류 변형 사이의 관계규명은 자동화 및 기계화를 위한 주요 요소로 생각된다. 본 연구는 그러한 관계를 규명하기 위하여 일련의 체계적인 과정을 제시하고 관계식을 제안하였다. 선상가열에 의한 변형은 3차원 열탄소성 변형현상으로 정식화될 수 있으며, 열탄소성 변형현상을 유한요소해석을 이용하여 다양한 가열조건에 대한 수치해석을 수행하였다. 유한요소법의 유용성을 검증하기 위하여 실험을 수행하였고 그 유용성을 확인하였다 변형관계식에 사용된 입력변수는 차원해석을 통하여 선정하였다. 유한요소법을 이용하여 얻어진 결과를 활용하여 선상가열에 의한 변형관계식을 추정하기 위하여 다변수해석과 다차원 보관과정을 예시하였다. 일련의 과정을 통하여 본 연구는 선상가열의 가열조건과 잔류 변형 사이의 관계식을 선정하기 위한 방법을 제안하였다.