• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.04a
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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.

• Wind and Structures
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• v.1 no.2
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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.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.2
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• pp.69-80
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• 2002

Sequential process of roll-bending and line heating has been used to deform the curved hull-plates in shipyards. A growing interest for the mechanization or automation of the line heating process has been noted. Relations between heating conditions and residual deformations are important components needed for the mechanization. The residual deformations are investigated by using a thermal elastic-plastic analysis based on the finite element analysis(FEA). Several experiments are also performed to examine the validity of the results of FEA. The input parameters of line heating are suggested by dimensional analysis of line heating. The dimensional analysis can extract the primary input-parameters of line heating. The relations between the heating conditions and the residual deformations are set up by multi-variate analysis and multiple-regression method. This study suggests a method for the relation between the heating conditions and the deformations lying under the line heating.

• IE interfaces
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• v.24 no.2
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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.

• Korean Journal of Child Studies
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• v.28 no.5
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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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• v.3 no.4
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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.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Journal of Korean Society for Atmospheric Environment
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• v.8 no.4
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• pp.213-220
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• 1992

Simple correlation analysis, factor analysis, and multi-variate analysis have been performed to analyze the relationship between air pollution and meteorological factors for air pollution and meteorological data measured at Kwanghwamun in Seoul during the period of one year(January 1990 $\sim$ December 1990). As a result of simple correlation and factor analysis, $SO_2$, TSP and CO concentrations have shown high negative correlation with temperature and among these indicating that these are related with pollutant emission trend based upon heating fuel usage. Ozone has a good corrleation with solar radiation and relative humidity to have a closed relation with $O_3$ generation reaction mechanism. The result of multi-variate correlation analysis shows that the concentration of $SO_2$ and CO are adequate for correlation model with ambient temperature and wind speed and $O_3$ concentrations are adequate for that with solar radiation and wind speed. $SO_2$ and CO levels are considered to be affected first of all by heating fuel usage as a emssion source and wind speed as a dispersion effect. The $SO_2$ concentration in the condition that the temperature fall below zero is explained by multilicative model with wind speed, only one variable.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.67-77
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• 2007

We tried new interpreting about the work of art in this paper. The work of art respects the intention of the artist to make it and interprets intention until now. After critics distinguish by a period, an area that they set to philosophical thought which is the time and interpreted. We set to each one subjectivity and interpreted between artist to make the work of art and appreciator. But in this paper, we tied various criteria which appreciates the work of art. We tried so that we presented the intimacy each other newly. Otherwise we tied with the subjectivity of the individual and are the try to be an objectification low through statistical technique. We looked into the culture and art in the introduction and explain the discussion about the work of art interpreting which the main subject. We set the category 6 area, and explain an each criteria explanation and assessment method. We tried to propose new interpreting as the intimacy to be multi-variate data analysis result of the assessment analysis.

• Journal of Korean Tunnelling and Underground Space Association
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• v.13 no.6
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• pp.531-555
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• 2011

This study aims to derive the statistical models for the estimation of the required specifications of a rock TBM as well as for its cutterhead design suitable for a given rock mass condition. From a series of multi-variate regression analysis of 871 TBM driving data and 51 linear rock cutting test results, the optimum models were newly proposed to consider a variety of rock properties and mechanical cutting conditions. When the derived models were applied to two domestic shield tunnels, their predictions of cutter penetration depth, cutter acting forces and cutter spacing were very close to real TBM driving data, showing their high applicability.