• Title/Summary/Keyword: Prediction of variables

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Drought Forecasting with Regionalization of Climate Variables and Generalized Linear Model

  • Yejin Kong;Taesam Lee;Joo-Heon Lee;Sejeong Lee
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.249-249
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    • 2023
  • Spring drought forecasting in South Korea is essential due to the sknewness of rainfall which could lead to water shortage especially in spring when managed without prediction. Therefore, drought forecasting over South Korea was performed in the current study by thoroughly searching appropriate predictors from the lagged global climate variable, mean sea level pressure(MSLP), specifically in winter season for forecasting time lag. The target predictand defined as accumulated spring precipitation(ASP) was driven by the median of 93 weather stations in South Korea. Then, it was found that a number of points of the MSLP data were significantly cross-correlated with the ASP, and the points with high correlation were regionally grouped. The grouped variables with three regions: the Arctic Ocean (R1), South Pacific (R2), and South Africa (R3) were determined. The generalized linear model(GLM) was further applied for skewed marginal distribution in drought prediction. It was shown that the applied GLM presents reasonable performance in forecasting ASP. The results concluded that the presented regionalization of the climate variable, MSLP can be a good alternative in forecasting spring drought.

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Artificial Neural Network Analysis for Prediction of Community Care Design Research in Spatial and Environmental Areas in Korea

  • Yumi, Jang;Jiyoung An;Jinkyung Paik
    • International Journal of Advanced Culture Technology
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    • v.11 no.2
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    • pp.249-255
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    • 2023
  • This study aims to empirically confirm the effect and impact of community care design research centered on domestic space and environment on health promotion, diagnosis treatment, disease management, rehabilitation, and mitigation through the year of publication and perspective. To this end, based on 1,227 space and environment design studies from 2,144 community care design research data conducted for about 20 years from 2002 to 2022, when care services began in earnest through the long-term care system for the elderly, SPSS 26.0 was used to create a 'Multi-layer Perceptron' artificial neural network structure model was predicted and neural network analysis was performed. Research Results First, as a result of checking studies in each field of health care by year, there is a significant difference with the number of studies related to health promotion being the highest. Second, the five perspectives are region, time, dimension, function, and content perspective. As a result of inputting these variables as independent variables and analyzing their importance in the artificial neural network, the function perspective had the most influence, followed by the region > content > dimension > time perspective.

Analysis about Developmental Changes of Children's Metamemory (아동의 메타기억의 발달적 변화에 관한 분석)

  • Park, Young-Ah
    • Korean Journal of Human Ecology
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    • v.16 no.6
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    • pp.1141-1152
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    • 2007
  • The purpose of this study was to investigate developmental changes of metamemory. The subjects were 120 5, 7, and 9 year-old children. All children performed metamemory tests which were composed of person variable, task variables, and strategy variable. There were significant age differences in metamemory awareness. As for person variable, prediction accuracy was increased with age. As for task variables, older children recognized aims of tasks, whereas younger children perceived salient properties of tasks. Also, as for strategy variable, number and complexity of strategy for memory retrieval were increased with age.

Development of Energy Consumption Estimation Model Using Multiple Regression Analysis (다중회귀분석을 활용한 하수처리시설 에너지 소비량 예측모델 개발)

  • Shin, Won-Jae;Jung, Yong-Jun;Kim, Ye-Jin
    • Journal of Environmental Science International
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    • v.24 no.11
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    • pp.1443-1450
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    • 2015
  • Wastewater treatment plant(WWTP) has been recognized as a high energy consuming plant. Usually many WWTPs has been operated in the excessive operation conditions in order to maintain stable wastewater treatment. The energy required at WWTPs consists of various subparts such as pumping, aeration, and office maintenance. For management of energy comes from process operation, it can be useful to operators to provide some information about energy variations according to the adjustment of operational variables. In this study, multiple regression analysis was used to establish an energy estimation model. The independent variables for estimation energy were selected among operational variables. The $R^2$ value in the regression analysis appeared 0.68, and performance of the electric power prediction model had less than ${\pm}5%$ error.

A Study on Prediction of Linear Relations Between Variables According to Working Characteristics Using Correlation Analysis

  • Kim, Seung Jae
    • International Journal of Internet, Broadcasting and Communication
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    • v.14 no.4
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    • pp.228-239
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    • 2022
  • Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

Numerical Prediction of the Outer Diameter for SAW Pipes Formed by Press-Brake Bending (프레스-브레이킹 굽힘 공정을 이용한 SAW 후육강관의 외경 예측을 위한 해석적 연구)

  • Park, G.B.;Kang, B.K.;Kang, B.S.;Ku, T.W.
    • Transactions of Materials Processing
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    • v.25 no.2
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    • pp.116-123
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    • 2016
  • Press-brake bending is used to shape flat and thick plates into a targeted circular configuration without excessive localized thinning or thickening. A brake bending press called 'a knife press bending apparatus' has been widely adopted to manufacture thick, large and long pipe from initially thick plate. Submerged Arc Welded (SAW) pipes are also produced by employing press-brake bending. These pipes are mainly used for oil, natural gas and water pipelines. The principal process variables for press-brake bending can be summarized as stroke of the press-brake knife, the distance between both roll in the lower die, and the feeding length of the plate. Many combinations of these process variables are available, thus various pipe diameters can be realized. In the current study, a series of repetitive numerical simulations by feeding a thick plate with initial thickness of 25.4mm were conducted with the consideration of elastic recovery. Furthermore, an index for SAW pipe production is proposed which can be widely used in industry.

The Effect of Process Variables on Strip Width Spread and Prediction in Hot Finish Rolling (열간 사상압연에서 스트립 폭 퍼짐의 공정변수 영향 및 예측에 관한 연구)

  • Jeon, J.B.;Lee, K.H.;Han, J.G.;Jung, J.W.;Kim, H.J.;Kim, B.M.
    • Transactions of Materials Processing
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    • v.25 no.4
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    • pp.235-241
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    • 2016
  • Dimensional accuracy of hot coil is improved by precise control of thickness profiles, flatness, width and winding profile. Especially, precise width control is important because yield could be increased significantly. Precise width control can be improved by predicting the amount of width spread. The purpose of this study is to develop the advanced prediction model for width spread in hot finish rolling for controlling width precisely. FE-simulations were performed to investigate the effect of process variables on width spread such as reduction ratio, forward and backward tension and initial width at each stand. From the statistical analysis of simulated data, advanced model was developed based on the existing models for strip width spread. The experimental hot rolling trials showed that newly developed model provided fairly accurate predictions on the strip width spread during the whole hot finishing rolling process.

An Investigation on Application of Experimental Design and Linear Regression Technique to Predict Pitting Potential of Stainless Steel

  • Jung, Kwang-Hu;Kim, Seong-Jong
    • Corrosion Science and Technology
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    • v.20 no.2
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    • pp.52-61
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    • 2021
  • This study using experimental design and linear regression technique was implemented in order to predict the pitting potential of stainless steel in marine environments, with the target materials being AL-6XN and STS 316L. The various variables (inputs) which affect stainless steel's pitting potential included the pitting resistance equivalent number (PRNE), temperature, pH, Cl- concentration, sulfate levels, and nitrate levels. Among them, significant factors affecting pitting potential were chosen through an experimental design method (screening design, full factor design, analysis of variance). The potentiodynamic polarization test was performed based on the experimental design, including significant factor levels. From these testing methods, a total 32 polarization curves were obtained, which were used as training data for the linear regression model. As a result of the model's validation, it showed an acceptable prediction performance, which was statistically significant within the 95% confidence level. The linear regression model based on the full factorial design and ANOVA also showed a high confidence level in the prediction of pitting potential. This study confirmed the possibility to predict the pitting potential of stainless steel according to various variables used with experimental linear regression design.

Subjective Evaluation of Wear Comfort and Related Physical Variables under Warm and Humid Condition (고온 다습한 환경에서의 주관적 착용 쾌적감과 관련 물성 변인)

  • Kim, Jeong-Hwa;Hong, Gyeong-Hui;Jo, Seung-Sik
    • Journal of the Korean Society of Clothing and Textiles
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    • v.21 no.6
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    • pp.1021-1030
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    • 1997
  • Physical variables related to the subjective evaluation of wear comfort were explored. Experimental fabrics was those used in the previous paper where subjective sensations of women's thin shirts were reported. Fabrics include 100% cotton (unfinished), 100% cotton (water repellent finished), cotton/polyester 35/65 (unfinished), cotton/polyester 35/65 (peach skin finished), 100% polyester fabric(plain), 100% polyester crepe. Among various physical properties of the experimental fabrics, heat 8E moisture transport properties and surface properties were chosen as important variables based on the regression coefficient. Especially, humidity at the microclimate in dynamic mode was highly correlated to the subjective evaluation and appeared to be a sensitive physical predictor, compared to dry thermal transmission rate or water vapor transmission rate. Surface characteristic parameters, however, did not show consistant trend in the prediction of the human's subjective sensation. Interaction between surface properties and humidity measurement was also observed.

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Selection of design variables in the Sandwich Beam for load resistance (하중에 대한 샌드위치보의 디자인 변수 선택)

  • Kim, Jongman;Hwang, Hyo-Kune;Lee, Jin-Woo;Kim, Wae-Yeule
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2002.10a
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    • pp.198-201
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    • 2002
  • It has been well-blown that sandwich structures are efficient to resist bending loads by increasing the moment of inertia of the panel. However, the accurate theoretical prediction of failure load and its optimization of sandwich beams for strength under concentrated loads were so complicated. Moreover, the appropriate selection of the variables, such as face thickness, core density and core thickness of the sandwich beam with many theories has continuously researched to satisfy for the given strength to weight structural requirement. There will be interesting to investigate the effect of those variables with its optimization for the load resistance.

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