• 제목/요약/키워드: Linear regression equation

검색결과 485건 처리시간 0.023초

비선형 회귀분석에 의한 엔드밀 가공조건에 따른 Al7075의 표면정도 예측 (Prediction of Surface Roughness of Al7075 on End-Milling Working Conditions by Non-linear Regression Analysis)

  • 조연상;박흥식
    • Tribology and Lubricants
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    • 제26권6호
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    • pp.329-335
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    • 2010
  • Recently, the End-milling processing is needed the high-precise technique to get a good surface roughness and rapid time in manufacturing of precision machine parts and electronic parts. The optimum surface roughness has an effect on end-milling working condition such as, cutting direction, spindle speed, feed rate and depth of cut, and so on. It needs to form the correlation of working conditions and surface roughness. Therefore this study was carried out to presume of surface roughness on end-milling working condition of Al7075 by regression analysis. The results was shown that the coefficient of determination($R^2$) of regression equation had a fine reliability of 87.5% and nonlinear regression equation of surface rough was made by multiple regression analysis.

초음파 속도법에 의한 현장 콘크리트 강도추정의 신뢰성 향상 (Reliability Improvement of In-Place Concreter Strength Prediction by Ultrasonic Pulse Velocity Method)

  • 원종필;박성기
    • 한국농공학회지
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    • 제43권4호
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    • pp.97-105
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    • 2001
  • The ultrasonic pulse velocity test has a strong potential to be developed into a very useful and relatively inexpensive in-place test for assuring the quality of concrete placed in structure. The main problem in realizing this potential is that the relationship between compressive strength ad ultrasonic pulse velocity is uncertain and concrete is an inherently variable material. The objective of this study is to improve the reliability of in-place concrete strength predictions by ultrasonic pulse velocity method. Experimental cement content, s/a rate, and curing condition of concrete. Accuracy of the prediction expressed in empirical formula are examined by multiple regression analysis and linear regression analysis and practical equation for estimation the concrete strength are proposed. Multiple regression model uses water-cement ratio cement content s/a rate, and pulse velocity as dependent variables and the compressive strength as an independent variable. Also linear regression model is used to only pulse velocity as dependent variables. Comparing the results of the analysis the proposed equation expressed highest reliability than other previous proposed equations.

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로우터리 경운(耕耘)의 부하특성(負荷特性) 및 소요동력(所要動力)에 관(関)한 연구(硏究) (Tilling Load Characteristics and Power Requirement for Rotary Tillers)

  • 최규홍;류관희
    • Journal of Biosystems Engineering
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    • 제9권2호
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    • pp.27-36
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    • 1984
  • This study was carried out to investigate the effects of the tilling depth, tilling travel speed and soil shear stress on the tilling load characteristics and power requirement for rotary tillers. The results obtained from the study are summarized as follows. 1. The average and maximum PTO torque increased as the tilling depth, tilling pitch and soil shear stress increased. A multiple linear regression equation to estimate the average PTO torque in terms of the above parameters was developed. 2. The ratios of maximum PTO torque to the average torque were in the range of 1.17 to 1.65 for the various tilling conditions tested. The variation in PTO torque increased greatly as the tilling pitch and soil shear stress increased, but decreased as the tilling depth increased. 3. Power requirement for the PTO shaft increased with the tilling depth, travel speed and soil shear stress, but decreased slightly as the tilling pitch increased. A multiple linear regression equation to estimate power requirement for the PTO shaft in terms of the above parameters was developed. 4. The specific power requirement for the rotary tiller was in the range of $0.008-0.015ps/cm^2$ for the various tilling conditons tested. The specific tilling capacity decreased as the tilling depth and soil shear stress increased, but increased with the tilling pitch. A multiple linear regression equation to estimate the specific tilling capacity in terms of the above parameters was developed.

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한우 혈청에서 호르몬 및 대사물질 농도들의 연령에 따른 변화에 관한 연구 (Change of Concentration of Hormones and Metabolic Materials in Serum by Age in Hanwoo)

  • 전기준;김종복;최재관;이창우;황정미;김형철;양부근;박춘근;나기준
    • 한국수정란이식학회지
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    • 제18권3호
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    • pp.215-225
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    • 2003
  • 본 시험은 한우에서 연령에 따라 혈청성분들의 변화를 알아보기 위하여 한우 866두(거세 638, 비거세 228)에 대하여 혈청 농도를 분석하여 채혈시 일령을 독립 변량으로 하고 혈청 성분들을 종속변수로 하는 다항 회귀방정식으로 추정한 결과는 다음과 같다. 거세우나 비거세우 모두 같은 차수의 회귀방정식이 접합한 혈청 성분은 IGF- I (3차식) calium(1차식) 및 IP(1차식)이었고 거세우에서는 1차식이 적합하고 비거세우에서는 3차식이 적합한 혈청 성분은 testosterone와 creatinine었다. 반면에 HDLC는 거세우에서는 3차식이 적합하나 비거세우에서는 1차식이 적합한 것으로 나타났다. 그리고 거세우에서는 2차식이 적합한데 비거세우에서는 3차식이 적합한 혈청성분은 triglyceride 농도와 globulin농도 그리고 A/G비율 등이었고, 거세우에서는 3차식이 적합하고 비거세우에서는 2차식이 적합한 혈청성분은 BUN이었으며, 거세우에서는 2차식이 적합한데 비거세우에서는 1차식이 적합한 혈청성분은 TP와 albumin이었다. 한편 cortisol은 거세우나 비거세우에서 모두 3차식까지의 회귀방정식으로는 연령에 따른 변화를 설명하기가 적합하지 않았으며 glucose는 비거세우에서는 3차식 변화를 보이고 있으나 거세우에서는 3차식까지의 회귀방정식만으로는 연령에 따른 변화를 설명하기가 어려웠다. 가장 적합한 것으로 판단되는 혈청성분들의 회귀모형 중에서 비교적 R-SQUARE 값이 높은 것(R-SQUARE value>0.1)들은 거세우에서 ICF-I, albumin, creatinine, IP, HDLC 등이었으며, 비거세우에서 testosterone, IGF-I, TP, albumin, glucose, creatinine, IP, HDLC 등으로 나타났다. 따라서 IGF-I, albumin, creatinine, IP, HDLC 등은 거세우나 비거세우 모두에서 연령에 따라 비교적 큰 변화를 보이는 혈청 성분이라고 생각된다.

불특정 공식손상을 가진 316L 스테인리스강의 기계적 물성치 예측을 위한 다중선형회귀 적용 (Application of Multiple Linear Regression to Predict Mechanical Properties of 316L Stainless Steel with Unspecified Pit Corrosion)

  • 정광후;김성종
    • Corrosion Science and Technology
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    • 제22권1호
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    • pp.55-63
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    • 2023
  • The aim of this study was to propose a multiple linear regression (MLR) equation to predict ultimate tensile strength (UTS) of 316L stainless steel with unspecified pit corrosion. Tensile specimens with pit corrosion were prepared using a potentiostatic acceleration test method. Pit corrosion was characterized by measuring ten factors using a confocal laser microscope. Data were collected from 22 tensile tests. At 85% confidence level, total pit volume, maximum pit depth, mean ratio of surface area, and mean area were significant factors showing linear relationships with UTS. The MLR equation using these three significant factors at a 85% confidence level showed considerable prediction performance for UTS. Determination coefficient (R2) was 0.903 with training and test data sets. The yield strength ratio of 316L stainless steel was found to be around 0.85. All specimens with a pit corrosion presented a yield ratio of approximately 0.85 with R2 of 0.998. Therefore, pit corrosion did not affect the yield ratio.

Prediction of apparent total tract digestion of crude protein in adult dogs

  • Kangmin Seo;Hyun-Woo Cho;Min Young Lee;Chan Ho Kim;Ki Hyun Kim;Ju Lan Chun
    • Journal of Animal Science and Technology
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    • 제66권2호
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    • pp.374-386
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    • 2024
  • To predict the apparent total tract digestibility (ATTD) of crude protein (CP) in dogs we developed an in vitro system using an in vitro digestion method and a statistical analysis. The experimental diets used chicken meat powder as the protein source, with CP levels of 20% (22.01%, analyzed CP value as dry-based), 30% (31.35%, analyzed CP value as dry-based), and 40% (41.34%, analyzed CP value as dry-based). To simulate in vivo digestive processes a static in vitro digestion was performed in two steps; stomach and small intestine. To analyze ATTD the total fecal samples were collected in eight neutered beagle dogs during the experimental period. CP digestibility was calculated by measuring CP levels in dog food, in vitro undigested fraction, and dog feces. In result, CP digestibility at both in vivo and in vitro was increased with increasing dietary CP levels. To estimate in vivo digestibility the co-relation of in vivo ATTD and in vitro digestibility was investigated statistically and a regression equation was developed to predict the CP ATTD (% = 2.5405 × in vitro CP digestibility (%) + + 151.8). The regression equation was evaluated its feasibility by using a commercial diet. The predicted CP digestibility which was calculated by the regression equation showed high index of similarity (100.16%) with that of in vivo in dogs. With that, it would be a feasible non-animal method to predict in vivo CP digestibility by using in vitro digestion method and the proposed linear regression equation in adult dogs.

전력수요예측을 위한 다양한 퍼지 최소자승 선형회귀 모델 (Various Models of Fuzzy Least-Squares Linear Regression for Load Forecasting)

  • 송경빈
    • 조명전기설비학회논문지
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    • 제21권7호
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    • pp.61-67
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    • 2007
  • 전력수요예측은 전력계통의 운용을 위해 필수적이다. 따라서 다양한 방법이 제시되어 왔으며, 특히 특수일의 수요예측은 평일과 구분되며, 부하 패턴을 축출하기에 충분한 자료 확보가 어려워 예측 오차가 크게 나타난다. 본 논문에서는 특수일의 부하예측 정확도를 개선하기 위해 퍼지 최소자승 선형회귀 모델을 분석한다. 4종류의 퍼지 최소자승 선형회귀 모델에 대해 분석과 사례연구를 통하여 가장 정확한 모델을 제시한다.

Price Monitoring Automation with Marketing Forecasting Methods

  • Oksana Penkova;Oleksandr Zakharchuk;Ivan Blahun;Alina Berher;Veronika Nechytailo;Andrii Kharenko
    • International Journal of Computer Science & Network Security
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    • 제23권9호
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    • pp.37-46
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    • 2023
  • The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

Joint parameter identification of a cantilever beam using sub-structure synthesis and multi-linear regression

  • Ingole, Sanjay B.;Chatterjee, Animesh
    • Structural Engineering and Mechanics
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    • 제45권4호
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    • pp.423-437
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    • 2013
  • Complex structures are usually assembled from several substructures with joints connecting them together. These joints have significant effects on the dynamic behavior of the assembled structure and must be accurately modeled. In structural analysis, these joints are often simplified by assuming ideal boundary conditions. However, the dynamic behavior predicted on the basis of the simplified model may have significant errors. This has prompted the researchers to include the effect of joint stiffness in the structural model and to estimate the stiffness parameters using inverse dynamics. In the present work, structural joints have been modeled as a pair of translational and rotational springs and frequency equation of the overall system has been developed using sub-structure synthesis. It is shown that using first few natural frequencies of the system, one can obtain a set of over-determined system of equations involving the unknown stiffness parameters. Method of multi-linear regression is then applied to obtain the best estimate of the unknown stiffness parameters. The estimation procedure has been developed for a two parameter joint stiffness matrix.

Hybrid Fuzzy Least Squares Support Vector Machine Regression for Crisp Input and Fuzzy Output

  • Shim, Joo-Yong;Seok, Kyung-Ha;Hwang, Chang-Ha
    • Communications for Statistical Applications and Methods
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    • 제17권2호
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    • pp.141-151
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    • 2010
  • Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.