• 제목/요약/키워드: multiple Regression analysis

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Machine learning-based regression analysis for estimating Cerchar abrasivity index

  • Kwak, No-Sang;Ko, Tae Young
    • Geomechanics and Engineering
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    • 제29권3호
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    • pp.219-228
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    • 2022
  • The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.

다중회귀모형을 이용한 104주 주 최대 전력수요예측 (Weekly Maximum Electric Load Forecasting Method for 104 Weeks Using Multiple Regression Models)

  • 정현우;김시연;송경빈
    • 전기학회논문지
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    • 제63권9호
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    • pp.1186-1191
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    • 2014
  • Weekly and monthly electric load forecasting are essential for the generator maintenance plan and the systematic operation of the electric power reserve. This paper proposes the weekly maximum electric load forecasting model for 104 weeks with the multiple regression model. Input variables of the multiple regression model are temperatures and GDP that are highly correlated with electric loads. The weekly variable is added as input variable to improve the accuracy of electric load forecasting. Test results show that the proposed algorithm improves the accuracy of electric load forecasting over the seasonal autoregressive integrated moving average model. We expect that the proposed algorithm can contribute to the systematic operation of the power system by improving the accuracy of the electric load forecasting.

연관규칙을 이용한 근골격계 질환 예방 - 다변량 로지스틱 회귀분석의 결과를 기반으로 - (Preventing the Musculoskeletal Disorders using Association Rule - Based on Result of Multiple Logistic Regression -)

  • 박승헌;이석환
    • 대한안전경영과학회지
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    • 제9권4호
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    • pp.29-38
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    • 2007
  • We adapted association rules of data mining in order to investigate the relation among the factors of musculoskeletal disorders and proposed the method of preventing the musculoskeletal disorders associated with multiple logistic regression in previous study. This multiple logistic regression was difficult to establish the method of preventing musculoskeletal disorders in case factors can't be managed by worker himself, i.e., age, gender, marital status. In order to solve this problem, we devised association rules of factors of musculoskeletal disorders and proposed the interactive method of preventing the musculoskeletal disorders, by applying association rules with the result of multiple logistic regression in previous study. The result of correlation analysis showed that prevention method of one part also prevents musculoskeletal disorders of other parts of body.

로터리 사고발생 위치별 사고모형 개발 (Developing Accident Models of Rotary by Accident Occurrence Location)

  • 나희;박병호
    • 한국도로학회논문집
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    • 제14권4호
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    • pp.83-91
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    • 2012
  • PURPOSES : This study deals with Rotary by Accident Occurrence Location. The purpose of this study is to develop the accident models of rotary by location. METHODS : In pursuing the above, this study gives particular attentions to developing the appropriate models using multiple linear, Poisson and negative binomial regression models and statistical analysis tools. RESULTS : First, four multiple linear regression models which are statistically significant(their $R^2$ values are 0.781, 0.300, 0.784 and 0.644 respectively) are developed, and four Poisson regression models which are statistically significant(their ${\rho}^2$ values are 0.407, 0.306, 0.378 and 0.366 respectively) are developed. Second, the test results of fitness using RMSE, %RMSE, MPB and MAD show that Poisson regression model in the case of circulatory roadway, pedestrian crossing and others and multiple linear regression model in the case of entry/exit sections are appropriate to the given data. Finally, the common variable that affects to the accident is adopted to be traffic volume. CONCLUSIONS : 8 models which are all statistically significant are developed, and the common and specific variables that are related to the models are derived.

연속강우시 산성우의 이온농도 변화에 관한 조사연구 (A Study on Ion Concentration Change of Acid Rain by the Succeeding Raintall)

  • 박경렬;김대선
    • 한국환경보건학회지
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    • 제16권2호
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    • pp.11-20
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    • 1990
  • To investigate ionic characteristics of acid rain by the succeeding rainfall. bulk precipitation was collected every each 5mm rainfall from march to october 1990 at Dae Jeon area. pH, sulfate nitrate, chloride, ammonium ion was measured and analyzed. The result was as follows: 1. The weighted average pH of rain was 5.1$\pm$ 0.72(4.15~7.6) and rain pH less than 5.5 was appeared 51.3% 2. Average ion concentrations of sulfate, nitrate, chloride and ammonium ion was 125.12 $\mu$eq/l, 62.38 $\mu$eq/l, 31.95 $\mu$eq/l, 66.6 $\mu$eq/l and rates of each anions was 57%, 28.4%, 14.6% and rate of sulfate by nitrate was 2 times. 3. There is no correlations time interval of rainfall and Ion concentration change. 4. From initial to 15mm rainfall, each ion concentrations were decreased. and average concentration of pH, SO$^{-2}_{4}$, Cl ion concentration was increased in the succeeding rainfall 5. Only sulfate ion was correlated by the simple regression analysis with pH except NO$^{-}_{3}$, Cl$^{-}$ and NH$_{4}^{+}$ Cl$^{-}$ correlation coefficient was very high at the multiple regression analysis with pH. 6. Simple & multiple correlation coefficient among anions and NH$^{+}_{4}$ was very high especially N$^{+}_{4}$ and SO$^{2-}_{4}$ at simple regression analysis and SO$^{-2}_{4}$ and NO$_{3}^{-}$, Cl$^{-}$, NH$_{4}^{-}$ at multiple regression analysis.

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환자만족도에 영향을 주는 환자경험 변인 탐색: 중회귀 및 수정된 ISA를 통하여 (Exploration of Variables Affecting Inpatient Experience Satisfaction: Using a Multiple-Regression and Revised ISA)

  • 서효정
    • 한국병원경영학회지
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    • 제27권2호
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    • pp.44-52
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    • 2022
  • Purposes: This study tried to extract variables affecting patient-experience satisfaction level in hospital situation, using a multiple-regression analysis and ISA(Revised Importance-Satisfaction Analysis), and to explore variables needed to be improved. Methodology: A mobile-based online patient-experience survey was conducted in eleven general hospitals in A city. To test the validity of this test, this data was compared with the data from Health-Insturance Review and Assessment Service. Then, the standardized regression coefficients extracted from a multiple-regression analysis were used as the importance scale to be used in ISA. Finding: Taken together, the areas with the highest contribution for the in-hospital patient-experience satisfaction level were medication and treatment process and hospital environment. In conclusion, the revised ISA which can show satisfaction and importance both with simultaneously and multi-axis way would be useful in hospital improvement activities. Practical Implications: This study tried to develop a mobile-based patient-experience survey, and to extract the major variables affecting patient-satisfaction level and to identify variables need to be improved. Finally, this should help hostipals to prepare the assessment process with various improvement activities.

사무소 건설의 설계변수 열성능 평가 및 부하예측방정식 개발 (Thermal Performance Evaluation of Design Parameters and Development of Load Prediction Equations of Office Buildings)

  • 석호태;김광우
    • 설비공학논문집
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    • 제13권9호
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    • pp.914-921
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    • 2001
  • The objective of this study is to evaluate the design parameters and to develop the cooling and heating load prediction equations of office buildings. The building load calculation simulation was carried out using the DOE-2.1E program. The results of the simulation was used as a data for ANOVA and multiple regression analysis which could develop the load prediction equations.

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주부의 소비자기능과 관련변수간의 인과관계 (The Causal Relationship of Homemakers' Consumer Function and the Related Variables)

  • 김미라
    • 가정과삶의질연구
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    • 제17권3호
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    • pp.131-144
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    • 1999
  • The purpose of this study was to examine the influences of the consumer's knowledge the consumer's attitude the family characteristics and the variables on consumer socialization to the consumer's functions of homemakers. The samples were selected from 428 homemakers living in Kwangju, Frequncies Perentiles Means Standard Deviations Multiple regression Path analysis were used as statistical analysis The results were sumarized as follows: Resulting from multiple regression analysis the consumer's function had the positive linear relationships with variables such as family life cycles interaction with family consume knowledge and consumer attitude. The most influential variable was consumer attitude.

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라울의 법칙과 다중회귀분석법에 의한 n-Nonane+n-Decane+n-Tridecane 계의 인화점 계산 (The Calculation of Flash Point for n-Nonane+n-Decane+n-Tridecane System by Raoult's Law and Multiple Regression Analysis)

  • 하동명;이성진
    • 한국가스학회지
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    • 제22권2호
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    • pp.52-58
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    • 2018
  • 가연성 액체 혼합물의 화재와 폭발의 위험성을 규정하는 가장 중요한 성질 중 하나는 인화점이다. 본 논문에서는 삼성분계 액체 혼합물인, n-nonane+n-decane+n-tridecane 계의 인화점을 Seta flash 밀폐식 장치를 사용하여 측정하였다. 실험값은 라울의 법칙을 이용한 방법과 다중회귀분석법에 의해 계산된 값들과 비교되었다. 라울의 법칙에 의한 계산된 결과의 절대평균오차는 $0.6^{\circ}C$이었다. 다중회귀분석법에 의해 계산된 결과의 절대평균 오차는 $0.4^{\circ}C$이었다. 절대평균오차에서 알 수 있듯이 다중회귀분석법에 의한 계산값이 라울의 법칙에 의한 계산값에 비해 측정값을 잘 모사하였다.