• Title/Summary/Keyword: 선형회귀 모델

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A Study on Emergency Node Detection Method based on Segmented Linear Regression (분할 선형 회귀를 이용한 Emergency node 감지 모델 연구)

  • Kim, Se-Jun;Lim, Hwan-Hee;Lee, Byung-Jun;Kim, Kyung-Tae;Youn, Hee-Yong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2018.07a
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    • pp.197-198
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    • 2018
  • 본 논문에서는 산업 IoT (IIoT) 환경에서 생산 설비 내 각 센서 노드의 데이터 이상 여부를 게이트웨이에서 판단하는 Emergency node 선정 모델을 제안하였다. 이 모델은 IIoT 환경이 적용된 생산 설비의 Emergency 상태 즉, 이상 동작으로 인한 온도, 진동 데이터 등의 비정상적인 수집을 구분하여 즉각적으로 대응할 수 있도록 하는 것을 목표로 한다. 본 논문에서는 분할 선형 회귀를 통하여 주기 내 데이터의 허용 범위를 계산하여 기존의 Threshold 방식보다 정확하고 범용적으로 Emergency node를 분류한다.

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Development of the Linear Regression Analysis Model to Estimate the Shear Strength of Soils (흙의 전단강도 산정을 위한 선형회귀분석모델 개발)

  • Lee, Moon-Se;Ryu, Je-Cheon;Kim, Kyeong-Su
    • The Journal of Engineering Geology
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    • v.19 no.2
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    • pp.177-189
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    • 2009
  • The shear strength has been managed as an important factor in soil mechanics. The shear strength estimation model was developed to evaluate the shear strength using only a few soil properties by the linear regression analysis model which is one of the statistical methods. The shear strength is divided into two part; one is the internal friction angle (${\phi}$) and the other is the cohesion (c). Therefore, some valid soil factors among the results of soil tests are selected through the correlation analysis using SPSS and then the model are formulated by the linear regression analysis based on the relationship between factors. Also, the developed model is compared with the result of direct shear test to prove the rationality of model. As the results of analysis about relationship between soil properties and shear strength, the internal friction angle is highly influenced by the void ratio and the dry unit weight and the cohesion is mainly influenced by the void ratio, the dry unit weight and the plastic index. Meanwhile, the shear strength estimated by the developed model is similar with that of the direct shear test. Therefore, the developed model may be used to estimate the shear strength of soils in the same condition of study area.

Determination of the Strength and Stiffness Degradation Factor for Circular R/C Bridge Piers (원형 철근콘크리트 교각의 강성 및 강도감소지수 결정)

  • 이대형;정영수
    • Journal of the Earthquake Engineering Society of Korea
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    • v.4 no.2
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    • pp.73-82
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    • 2000
  • 본연구의 목적은 반복하중을 받는 철근콘크리트 교량 교각의 비선형 이력거동을 해석적으로 예측하는 것이다 이를 위해서 반복적인 횡하중이 작용하는 경우에 실험결과와 일치하는 교각의 하중-변위 이력곡선을 도출하고자 수정된 trilinar 이력거동모델을 이용하였다 철근과 콘크리트의 비선형 거동특성과 각 하중단계에 따른 교각의 중립축을 구하여 소성힌지부의 모멘트와 변형률을 구하고 반복하중하에서의 강성의 변화를 해석적으로 모형화하기 위하여 각기 다른 강성을 갖는 5가지 지선을 갖춘 형태의 이력거동모델식을 제안하였다 본 연구에서는 실험적으로 구한 하중-변위 이력곡선을 이용하여 축하중비 주철근비 및 구속철근비에 따른 강도감소지수와 강성감소지수의 영향을 회귀분석을 이용하여 일반식으로 제안하였다 새로운 이력거동 해석 모델을 프로그램 SARCF III에 적용함으로써 기존 철근콘크리트 교각에 강도 및 강성감소 현상을 정확하게 예측하였다

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Estimation of surface nitrogen dioxide mixing ratio in Seoul using the OMI satellite data (OMI 위성자료를 활용한 서울 지표 이산화질소 혼합비 추정 연구)

  • Kim, Daewon;Hong, Hyunkee;Choi, Wonei;Park, Junsung;Yang, Jiwon;Ryu, Jaeyong;Lee, Hanlim
    • Korean Journal of Remote Sensing
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    • v.33 no.2
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    • pp.135-147
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    • 2017
  • We, for the first time, estimated daily and monthly surface nitrogen dioxide ($NO_2$) volume mixing ratio (VMR) using three regression models with $NO_2$ tropospheric vertical column density (OMIT-rop $NO_2$ VCD) data obtained from Ozone Monitoring Instrument (OMI) in Seoul in South Korea at OMI overpass time (13:45 local time). First linear regression model (M1) is a linear regression equation between OMI-Trop $NO_2$ VCD and in situ $NO_2$ VMR, whereas second linear regression model (M2) incorporates boundary layer height (BLH), temperature, and pressure obtained from Atmospheric Infrared Sounder (AIRS) and OMI-Trop $NO_2$ VCD. Last models (M3M & M3D) are a multiple linear regression equations which include OMI-Trop $NO_2$ VCD, BLH and various meteorological data. In this study, we determined three types of regression models for the training period between 2009 and 2011, and the performance of those regression models was evaluated via comparison with the surface $NO_2$ VMR data obtained from in situ measurements (in situ $NO_2$ VMR) in 2012. The monthly mean surface $NO_2$ VMRs estimated by M3M showed good agreements with those of in situ measurements(avg. R = 0.77). In terms of the daily (13:45LT) $NO_2$ estimation, the highest correlations were found between the daily surface $NO_2$ VMRs estimated by M3D and in-situ $NO_2$ VMRs (avg. R = 0.55). The estimated surface $NO_2$ VMRs by three modelstend to be underestimated. We also discussed the performance of these empirical modelsfor surface $NO_2$ VMR estimation with respect to otherstatistical data such asroot mean square error (RMSE), mean bias, mean absolute error (MAE), and percent difference. This present study shows a possibility of estimating surface $NO_2$ VMR using the satellite measurement.

The study On Linear Regression Model At One Component Input System) (성분입력계의 선형회귀모델에 관한 연구)

  • 김치홍;주영수
    • Proceedings of the Korea Water Resources Association Conference
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    • 1990.07a
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    • pp.167-174
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    • 1990
  • 일종의 Autoregression Model에 강우와 유량의 입력에 의하여 일유입량의 예측을 행한 것으로 댐 지점의 일유입량과 우량시계열을 회귀분석하여 댐 유역의 하천유량을 예측 할 수 있는 수학적 모형을 수립하고 통계적 분석을 행 하고자 한다.

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Calculating the Uniaxial Compressive Strength of Granite from Gangwon Province using Linear Regression Analysis (선형회귀분석을 적용한 강원도 지역 화강암의 일축압축강도 산정)

  • Lee, Moon-Se;Kim, Man-Il;Baek, Jong-Nam;Han, Bong-Koo
    • The Journal of Engineering Geology
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    • v.21 no.4
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    • pp.361-367
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    • 2011
  • The uniaxial compressive strength (UCS) is an important factor in the design and construction of surface and underground structures. However, the method employed to measure UCS is time consuming and expensive to apply in the field. Therefore, we developed a model to estimate UCS based on a few properties using linear regression analysis, which is a statistical method. To develop the model, valid factors from the test results were selected from a correlation analysis using a statistical program, and the model was formulated by linear regression based on the relationships among factors. UCS estimates derived from the model were compared with the results of UCS tests, to assess the reliability of the model. The relationship between rock properties and UCS indicates that the factors with the greatest influence on UCS are point load strength and shape facto r. The UCS values obtained using the model are in good agreement with the results of the UCS test. Therefore, the developed model may be used to estimate the UCS of rocks in regions with similar conditions to those of the present study area.

An Analysis Study for Optimal Uptake of Nutrient Solution Based on Multiple Linear Regression Model in Strawberry Hydroponic Environments (딸기 수경 재배 환경에서의 다중 선형 회귀 모델 기반의 양액 적정 흡수량 분석 연구)

  • Lim, Jong-Hyun;Lee, Myeong-Bae;Cho, Hyun-Wook;Shin, Chang-Sun;Park, Chang-Woo;Cho, Yong-Yun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.578-580
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    • 2019
  • 우리 나라의 딸기 수경재배 면적은 2002년 5ha로 시작해서, 2007년에는 84ha, 2012년에는 317ha, 2017년에 1,575ha로 매년 30% 이상 급속하게 성장하고 있다. 이런 경향은 수경재배가 토양재배보다 작업이 용이하여 노동시간이 절약되며, 수량을 더 많이 생산할 수 있기 때문이다. 하지만, 공급양액을 배액으로 흘려버리는 비순환식 수경재배 방식이 증가 하면서 환경오염을 유발시킬 뿐만 아니라 수경재배 운영비용의 증가를 가져오고 있다. 본 논문은 작물 생장에 최적화된 양액공급을 위해 상관관계 분석 및 다중 선형 회귀 모델 기반의 딸기 수경재배 환경에서의 최적 양액 흡수량을 분석하고 추정해 보았다. 분석 결과, 수경재배 환경정보(일사량, 온도, 습도, CO2 등)를 대상으로 일사량 및 온도가 습도 및 CO2에 비해 딸기재배를 위한 양액 흡수량에 더 큰 영향을 주는 것으로 분석되었고, 다중 선형 회귀 모델을 통한 회귀식의 R-Square값은 0.358으로 나타났다.

Development of Models for Estimating Growth of Quinoa (Chenopodium quinoa Willd.) in a Closed-Type Plant Factory System (완전제어형 식물공장에서 퀴노아 (Chenopodium quinoa Willd.)의 생장을 예측하기 위한 모델 개발)

  • Austin, Jirapa;Cho, Young-Yeol
    • Journal of Bio-Environment Control
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    • v.27 no.4
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    • pp.326-331
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    • 2018
  • Crop growth models are useful tools for understanding and integrating knowledge about crop growth. Models for predicting plant height, net photosynthesis rate, and plant growth of quinoa (Chenopodium quinoa Willd.) as a leafy vegetable in a closed-type plant factory system were developed using empirical model equations such as linear, quadratic, non-rectangular hyperbola, and expolinear equations. Plant growth and yield were measured at 5-day intervals after transplanting. Photosynthesis and growth curve models were calculated. Linear and curve relationships were obtained between plant heights and days after transplanting (DAT), however, accuracy of the equation to estimate plant height was linear equation. A non-rectangular hyperbola model was chosen as the response function of net photosynthesis. The light compensation point, light saturation point, and respiration rate were 29, 813 and $3.4{\mu}mol{\cdot}m^{-2}{\cdot}s^{-1}$, respectively. The shoot fresh weight showed a linear relationship with the shoot dry weight. The regression coefficient of the shoot dry weight was 0.75 ($R^2=0.921^{***}$). A non-linear regression was carried out to describe the increase in shoot dry weight of quinoa as a function of time using an expolinear equation. The crop growth rate and relative growth rate were $22.9g{\cdot}m^{-2}{\cdot}d^{-1}$ and $0.28g{\cdot}g^{-1}{\cdot}d^{-1}$, respectively. These models can accurately estimate plant height, net photosynthesis rate, shoot fresh weight, and shoot dry weight of quinoa.

One-dimensional Positioning using Iterative Linear Regression Based on Received Signal Strength and Mobility Information (반복선형회귀를 이용한 수신 신호 세기와 이동성 정보에 기반한 1차원 위치 추정)

  • Lee, Dong-Jun;Kim, Da-Yeong;Lee, Eun-Hye
    • Journal of Advanced Navigation Technology
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    • v.24 no.2
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    • pp.128-133
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    • 2020
  • In this study, an 1-dimensional positioning method using iterative linear regression for path loss expression is proposed. In the proposed method, received signal strengths (RSS) measured in several locations and distances between the measuring locat ions obtained by dead reckoning are used to derive a linear regression for the path loss from the transmitting beacon. In the proposed method, for the distance between the transmitting beacon and a target measuring location, several tentative values are assumed. For each tentative value, a linear regression is obtained. Among the linear regression expressions, the one closest to the known reference RSS value is selected and used to derive the distance to the target location. Test results show that the proposed method is more accurate than path loss model.