• Computers and Concrete
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• v.12 no.2
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• pp.151-167
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• 2013

Prediction of concrete properties is an important issue for structural engineers and different methods are developed for this purpose. Most of these methods are based on experimental data and use measured data for parameter estimation. Three typical methods of output estimation are Categorized Linear Regression (CLR), Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN). In this paper a statistical cleansing method based on CLR is introduced. Afterwards, MLR and ANN approaches are also employed to predict the compressive strength of structural lightweight aggregate concrete. The valid input domain is briefly discussed. Finally the results of three prediction methods are compared to determine the most efficient method. The results indicate that despite higher accuracy of ANN, there are some limitations for the method. These limitations include high sensitivity of method to its valid input domain and selection criteria for determining the most efficient network.

• Journal of the Korean Solar Energy Society
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• v.32 no.2
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• pp.28-34
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• 2012

It is necessary to estimate the regression coefficients in order to predict the daily global radiation on a horizontal surface. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for 16 different areas over Korea by estimating the regression coefficients taking into account cloud hours of bright sunshine. Particularly, the multiple linear regression model proposed shows reliable results for estimating the global radiation on a horizontal surface with monthly average deviation of-0.26 to +0.53% and each station annual average deviation of -1.61 to +1.7% from measured values.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.4
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• pp.428-436
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• 2014

This paper proposes a statistical regression method for classifying pillars and vehicles in parking area using a single ultrasonic sensor. There are three types of information provided by the ultrasonic sensor: TOF, the peak and the width of a pulse, from which 67 different features are extracted through segmentation and data preprocessing. The classification using the multiple SVM and the multinomial logistic regression are applied to the set of extracted features, and has achieved the accuracy of 85% and 89.67%, respectively, over a set of real-world data. The experimental result proves that the proposed feature extraction and classification scheme is applicable to the object classification using an ultrasonic sensor.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.914-918
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• 2004

The random regression model methodology was applied into the estimation of genetic parameters for body weights in Chinese Simmental cattle to replace the traditional multiple trait models. The variance components were estimated using Gibbs sampling procedure on Bayesion theory. The data were extracted for Chinese Simmental cattle born during 1980 to 2000 from 6 national breeding farms, where records from 3 months to 36 months were only used in this study. A 3 orders Legendre polynomial was defined as the submodel to describe the general law of that body weight changing with months of age in population. The heritabilities of body weights from 3 months to 36 months varied between 0.31 and 0.48, where the heritabilities from 3 months to 12 months slightly decreased with months of age but ones from 13 months to 36 months increased with months of age. Specially, the heritabilities at eighteenth and twenty-fourth month of age were 0.33 and 0.36, respectively, which were slightly greater than 0.30 and 0.31 from multiple trait models. In addition, the genetic and phenotypic correlations between body weights at different month ages were also obtained using regression model.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.1
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• pp.76-83
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• 2016

The various model tests are carried out to estimate and verify a ship performance in the design stage. But in view of the cost, the model test should be applied to every project vessel is very inefficient. Therefore, other methods of predicting the maneuverability with confined data are required at the initial design stage. The purpose of this study is to estimate the hydrodynamic derivatives by using the multiple regression analysis and PMM test data. The characteristics of the stern shape which has an important effect on the maneuverability are applied to the regression analysis in this study. The correlation analysis is performed to select the proper hull form coefficients and stern shape factors used as the variables in the regression analysis. The comparative analysis of estimate results and model test results is conducted on two ships to investigate the effectiveness of the maneuvering hydrodynamic derivatives estimation applied the stern shape. Through the present study, it is verified that the estimation using the stern shape factors as the variables are valid when the stern shape factors are located in the center of the database.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.5
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• pp.1-13
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• 2020

The empty houses' problem is important in the local revitalization and local sustainability, and these phenomenon caused by various factors of the region. The population and housing census data are the most effective data available to study this phenomenon by small regions. In this study, logistic regression and multiple regression analysis were performed to understand the effects of population, household, and housing characteristics on empty houses using population and housing census data. Also, the scale and direction of the effect of each characteristic in large cities, small cities, and rural areas were compared. As results, there was a slight difference between cities and province regions in the district and housing characteristic variables. In the comparison of Eup-Myeon-Dong, the affected variables were different in the Dong and Myeon areas. The significance of this study is to examine the effect of the characteristics of population and housing on the vacant houses and to confirm that the factors affecting different regions.

• Journal of Fashion Business
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• v.10 no.2
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• pp.181-193
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• 2006

The purpose of this study was to examine which factors among addiction buying behavior had been affected by body image. 235 female college students were surveyed for this study. For data analysis, descriptive statistics, $x^2$-test, multiple regression were used. As the results, generally there were significantly correlated among body image, diet addiction, binge eating, cosmetic surgery addiction, compulsive behavior and shoplift tendencies. Multiple regression results revealed that diet addiction, cosmetic surgery addiction, binge eating accounted for 34.8% of the explained variance in weight obsession. Also, regression results indicated that cosmetic surgery addiction, self-esteem, and diet addiction, and cosmetic surgery obession accounted for 20.4% of the explained variance in appearance orientation. Finally, regression results pointed out that self-esteem and diet obession accounted 22.3% of the explained variance in appearance evaluation. Based on these results, fashion marketing strategies would be suggested.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.4
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• pp.269-273
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• 2006

Multiple linear regression analysis was conducted to interpretate the relationship between sesame grain yield and its components under early sowing cropping condition. The t test showed that stem length, number of capsules per plant, 1000 seeds weight and seed weight per plant gave significant contribution to sesame grain yield, therefore those variables were assumed to mostly influenced components to grain yield of sesame. In the stepwise regression analysis, the predicted equation for sesame grain yield per square meter (Y) was Y = -7.900 + 0.150X1 + 0.461X5 + 15.553X6 + 8.543X7. Meanwhile, F value showed that stem length, number of capsules per plant and seed weight per plant gave significant contribution to sesame grain yield, while 1000 seeds weight did not significantly show. Based on the results, it is reasonable to assume that high yield. potential of sesame under early sowing cropping condition would be obtained by selecting breeding lines with long stem length, number of capsules per plant, and seed weight per plant, which was different result at the late sowing cropping condition in which days to flowering and maturity were assumed to be more affected factors to the sesame grain yield.

• Water for future
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• v.17 no.2
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• pp.107-112
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• 1984

It si presented here that in order to estimate reservoir sedimentation rate through the use of reservoir survey data of 66 irrigation reservoir in 3 major watersheds in this country, the correlation between reservoir sedimentation rate and the following factors; watershed area, trap-efficiency, watershed slope, shape factor of water shed, and reservoir deposition age in two models simple regression model and multiple regression model. Appropriatness of the proposed models have been calibrated from the survey data and as a result, it has been determined that the multiple regression model is much more accurate than the simple regression model. The annual sediment yield is correlated with watershed area and reservoir trap efficiency. It has been found that variation of the annual average sedimentation rate and the annual reservoir capacity loss rate are influenced by the trap efficiency of reservoir.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.189-199
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• 2020

This paper studies a Bayesian ordered multiple linear regression model with skew normal error. It is reasonable that the kind of inherent information available in an applied regression requires some constraints on the coefficients to be estimated. In addition, the assumption of normality of the errors is sometimes not appropriate in the real data. Therefore, to explain such situations more flexibly, we use the skew-normal distribution given by Sahu et al. (The Canadian Journal of Statistics, 31, 129-150, 2003) for error-terms including normal distribution. For Bayesian methodology, the Markov chain Monte Carlo method is employed to resolve complicated integration problems. Also, under the improper priors, the propriety of the associated posterior density is shown. Our Bayesian proposed model is applied to NZAPB's apple data. For model comparison between the skew normal error model and the normal error model, we use the Bayes factor and deviance information criterion given by Spiegelhalter et al. (Journal of the Royal Statistical Society Series B (Statistical Methodology), 64, 583-639, 2002). We also consider the problem of detecting an influential point concerning skewness using Bayes factors. Finally, concluding remarks are discussed.