• Journal of Digital Convergence
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• v.18 no.12
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• pp.481-488
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• 2020

Symbolic regression is an analysis method that directly generates a function that can explain the relationsip between dependent and independent variables for a given data in regression analysis. Genetic Programming is the leading technology of research in this field. It has the advantage of being able to directly derive a model that can be interpreted compared to other regression analysis algorithms that seek to optimize parameters from a fixed model. In this study, we propse a symbolic regression algorithm using parallel genetic programming based on a coarse grained parallel model, and apply the proposed algorithm to PMLB data to analyze the effectiveness of the algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.6
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• pp.781-792
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• 1998

The purpose of this study was to investigate the factors related to the propensity for symbolic consumption and the effects of materialism, reference group, and social stratification on the symbolic consumption in clothing. Data were administered to 957 adolescence in middle, high school, and college student living in Seoul, Chonju, Sunchon, Yousu, and Kwangyang from May to June 1997. For analysis of the data, frequencies, percentage, means, standard deviation, factor analysis, 1-test, one-way anomia, duncan's multiple range test, and multiple regression analysis were employed. The results of this study can be summarized asfollows. 1) Symbolic consumption, materialism, and reference group were found to have the significant differences according to social stratification groups by objectivemethod. The higher social stratification is, the higher symbolic consumption, materialism, and reference group were. 2) symbolic consumption were proven to have the significant differences according to materiaiism and reference group. The higher materialism and the influence of referencegroup indicated, the higher symbolic consumption. 3)according to the results of the regression analysis examining the relative influences of variables affecting symbolic consumption in clothing, the relative importance of the variables are in order of : the influences of the reference group, materialism, social stratification, status inconsistency type (occupation-income), and their explanatory power totalled 40.0%.

• Journal of the Korean Home Economics Association
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• v.36 no.10
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• pp.131-144
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• 1998

The purpose of this study was to examine the differences of symbolic consumption of adolescents, and the effects of demographic factors on the symbokic consumption in clothing. Data were administered to 957 adolescents in middle, high school, and college students living in Seoul, Chonju, Sunchon, Yousu, and Kwangyang from May to June 1997. For analysis of the data, factor analysis, t-test, one-way ANOCA, duncan's multiple range test, and multiple regression analysis were employed. The results of this study were summarized as follows. 1) Symbolic consumption in colthing were shown to have the significant differences accoding to age, gender, the level of urbanization, parent's education, father's occupation, social stratification groups. The higher the age, the level of urbanization, and parent's education, father's occupation, social stratification is, or the female, the higher is symbolic consumption in clothing. 2) According to the results of the regression analysis examining the rerlative influences of variables affecting symbolic consumption in clothing, the relative importance of the variables are in order of; income, gender, age, mother's education, residence, and their explanatory powere totalled 11.5%.

• Computers and Concrete
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• v.20 no.1
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• pp.65-75
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• 2017

In this study, a novel application of symbolic regression (SR) is employed for the prediction of ultimate shear strength of steel fiber reinforced (SFRC) and glass fiber reinforced (GFRC) corbels without stirrups, for the first time in the literature. A database is created using the test results (42 tests) conducted by the authors of current paper as well as the previous studies available in the literature. A symbolic regression based empirical formulation is proposed using this database. The formulation is unique in a way that it has the capability to predict the shear strength of both SFRC and GFRC corbels. The performance of proposed model is tested against randomly selected testing set. Additionally, a parametric study with a wide range of variables is carried out to test the effect of each parameter on the shear strength. The results confirm the high prediction capacity of proposed model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.730-735
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• 2014

This paper introduces a GP (Genetic Programming) based robust technique for the prediction of a heavy rain newsflash. The nature of prediction for precipitation is very complex, irregular and highly fluctuating. Especially, the prediction of heavy precipitation is very difficult. Because not only it depends on various elements, such as location, season, time and geographical features, but also the case data is rare. In order to provide a robust model for precipitation prediction, a nonlinear and symbolic regression method using GP is suggested. The remaining part of the study is to evaluate the performance of prediction for a heavy rain newsflash using a GP based nonlinear regression technique in Korean regions. Analysis of the feature selection is executed and various fitness functions are proposed to improve performances. The KLAPS data of 2006-2010 is used for training and the data of 2011 is adopted for verification.

• Fashion & Textile Research Journal
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• v.10 no.4
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• pp.499-505
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• 2008

The Purpose of this study is to research the relations between brand attachment and brand loyalty depending on symbolic consumption propensity toward fashion goods. Subjects were 391 women in their twenties to fifties who live in Gyungsang Province and have purchased the fashion goods. Frequency analysis, reliability analysis, factor analysis, multiple regression analysis, and one-way layout variance analysis were conducted using SPSS 13.0 as data analysis. The findings from the analysis are described in the following: Uniqueness and materialism out of the symbolic consumption propensity toward fashion goods had positive effects on the elements of brand attachment such as love, care, and knowledge. Brand loyalty was influenced positively by social face sensitivity and materialism among symbolic consumption toward fashion goods.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.12 s.138
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• pp.1562-1570
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• 2004

The main purpose of this study was to investigate the elements which influence the symbolic consumption in clothing. Materialism and agent of socialization have been studied and the affect of these two are also developed. The theoretical study and survey methods were used. The survey was administered to 426 women in their twenties living in Seoul and Kyungki region. SPSS packages were applied to find out the results of ANOVA Duncans multiple range tests, means, standard deviation, factor analysis, and regression analysis. The major findings of this study could be summerized as follows; First, the subordinate parts of symbolic consumption was divided into these three parts; fashion oriented consumption, brand oriented consumption, hedonic consumption. The average of hedonic consumption was higher than other subordinate parts of symbolic consumption. Second, symbolic consumption was seemed to have the differences according to materialism and its subfactors. The higher materialism indicated, the higher symbolic consumption was. Third, symbolic consumption was proven to have the differences according to agent of socialization such as reference group and mass media. The higher the influence of the reference group and mass media was, the higher symbolic consumption was. Fourth, according to the results of the regression analysis examing the relative influences of variables affecting symbolic consumption in clothing, the influence of the reference group was the most important variable. The influence of mass media and materialism was related positively to the symbolic consumption.

• Steel and Composite Structures
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• v.43 no.3
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• pp.293-309
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• 2022

Accurate design models for predicting the shear resistance of headed studs in solid concrete slabs are essential for obtaining economical and safe steel-concrete composite structures. In this study, symbolic regression with genetic programming (GPSR) was applied to experimental data to formulate new descriptive equations for predicting the shear resistance of studs in solid slabs using both normal and lightweight concrete. The obtained GPSR-based nominal resistance equations demonstrated good agreement with the test results. The equations indicate that the stud shear resistance is insensitive to the secant modulus of elasticity of concrete, which has been included in many international standards following the pioneering work of Ollgaard et al. In contrast, it increases when the stud height-to-diameter ratio increases, which is not reflected by the design models in the current international standards. The nominal resistance equations were subsequently refined for use in design from reliability analyses to ensure that the target reliability index required by the Eurocodes was achieved. Resistance factors for the developed equations were also determined following US design practice. The stud shear resistance predicted by the proposed models was compared with the predictions from 13 existing models. The accuracy of the developed models exceeds the accuracy of the existing equations. The proposed models produce predictions that can be used with confidence in design, while providing significantly higher stud resistances for certain combinations of variables than those computed with the existing equations given by many standards.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.270-272
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• 2006

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.

• Journal of the Korean Home Economics Association
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• v.42 no.8
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• pp.123-132
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• 2004

The purpose of this research was to determine the relation between clothing evaluative criteria and personality types. Primary factor analysis was used to classify the clothing evaluative criteria and the continual scores of Myers Briggs Type Indicator (MBTI) were used for classifying the personality types. Correlation analysis and multiple regression analysis were used to determine the relation between the clothing evaluative criteria and the personality types. The data for this research were collected from questionnaires of 309 female university students in Seoul. In the results, the clothing evaluative criteria were grouped into 4 underlying dimensions： practical, situational, appearance producible and symbolic. Partially significant relations between the 4 clothing evaluative criteria and the 4 indicators of MBTI personality types were found through correlation analysis. Multiple regression analysis revealed that the variables explaining the dimension of Sensing and Intuition (SN) were appearance producible and symbolic clothing evaluative criteria; the appearance producible criterion had an inclination toward Intuition while the symbolic criterion had an inclination toward Sensing. The variable explaining the dimension of Judging and Perceiving (JP) was situational clothing evaluative criterion, which had an inclination toward Judging.