• Title/Summary/Keyword: Multiple Linear

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Orographic Precipitation Analysis with Regional Frequency Analysis and Multiple Linear Regression (지역빈도해석 및 다중회귀분석을 이용한 산악형 강수해석)

  • Yun, Hye-Seon;Um, Myoung-Jin;Cho, Won-Cheol;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.42 no.6
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    • pp.465-480
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    • 2009
  • In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

SNR Enhancement Algorithm Using Multiple Chirp Symbols with Clock Drift for Accurate Ranging

  • Jang, Seong-Hyun;Kim, Yeong-Sam;Yoon, Sang-Hun;Chong, Jong-Wha
    • ETRI Journal
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    • v.33 no.6
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    • pp.841-848
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    • 2011
  • A signal-to-noise ratio (SNR) enhancement algorithm using multiple chirp symbols with clock drift is proposed for accurate ranging. Improvement of the ranging performance can be achieved by using the multiple chirp symbols according to Cramer-Rao lower bound; however, distortion caused by clock drift is inevitable practically. The distortion induced by the clock drift is approximated as a linear phase term, caused by carrier frequency offset, sampling time offset, and symbol time offset. SNR of the averaged chirp symbol obtained from the proposed algorithm based on the phase derotation and the symbol averaging is enhanced. Hence, the ranging performance is improved. The mathematical analysis of the SNR enhancement agrees with the simulations.

MULTIPLE SOLUTIONS FOR THE NONLINEAR HAMILTONIAN SYSTEM

  • Jung, Tacksun;Choi, Q-Heung
    • Korean Journal of Mathematics
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    • v.17 no.4
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    • pp.507-519
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    • 2009
  • We give a theorem of the existence of the multiple solutions of the Hamiltonian system with the square growth nonlinearity. We show the existence of m solutions of the Hamiltonian system when the square growth nonlinearity satisfies some given conditions. We use critical point theory induced from the invariant function and invariant linear subspace.

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Adaptive Two Dimensional Linear Prediction Algorithm For Estimating Incident Angles of Multiple Broadbamd Signals. (다수의 광대역 신호의 입사각 추정을 위한 이차원의 정응선형예측 알고리즘)

  • 김태원
    • Proceedings of the Acoustical Society of Korea Conference
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    • 1987.11a
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    • pp.61-65
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    • 1987
  • An algorithm for estimating incident angles of multiple broaband signals is proposed. The method adopts semicausal model for two dimensional linear prediction filter coefficients such that the arithmatic averag of the mean squared values of the forward and reverse prediction arrors is minimized. Preliminary results demonstrating the performance of the proposed method are presented. Simulation results indicate that the performance depends on signal-to-noise ratio and prediction order in spatial demension.

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Multiple Objective Linear Programming with Minimum Levels and Trade Offs through the Interactive Methods

  • Chun, Man-Sul;Kim, Man-Sik
    • Journal of the military operations research society of Korea
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    • v.13 no.1
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    • pp.116-124
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    • 1987
  • This paper studies to develop the procedure which is combined by the progressive goals and progressive weights generation method. This procedure minimizes the number of questions the decision maker has to make, and also satisfies the generated minimum goal of each objective function. With the procedure developed, we are able to improve the previous multiple objective linear programming techniques in two points.

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Procedures for Detecting Multiple Outliers in Linear Regression Using R

  • Kwon, Soon-Sun;Lee, Gwi-Hyun;Park, Sung-Hyun
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.13-17
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    • 2005
  • In recent years, many people use R as a statistics system. R is frequently updated by many R project teams. We are interested in the method of multiple outlier detection and know that R is not supplied the method of multiple outlier detection. In this talk, we review these procedures for detecting multiple outliers and provide more efficient procedures combined with direct methods and indirect methods using R.

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Estimation of AADT Using Multiple Linear Regression in Isolated Area (다중선형 회귀분석을 이용한 고립지역에서의 AADT 추정방안 연구)

  • Kim, Tae-woon;Oh, Ju-sam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.35 no.4
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    • pp.887-896
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    • 2015
  • This study estimates future AADT using historical AADT and socio-economic factors in isolated area. Multiple linear regression method by socio-economic factors are lower MAPE and higher R-square than using historical AADT. Analysis of socio-economic factors influence AADT in isolated typical areas, varied socio-economic factors influence on AADT. In isolated coastal areas, oil price influence on AADT. AADT forecasting model in isolated area is excellent when analysising $R^2$ and MAPE. It is assume that estimation of AADT in isolated area using multiple linear regression is accurate because of a little passed traffic volume and traffic volume fluctuation.

Comparison of Data-based Real-Time Flood Forecasting Model (자료기반 실시간 홍수예측 모형의 비교·검토)

  • Choi, Hyun Gu;Han, Kun Yeun;Roh, Hong Sik;Park, Se Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.5
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    • pp.1809-1827
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    • 2013
  • Recently we need to take various measures to prepare for extreme flood that occur due to climate change. It is important that establish flood forecasting system to prepare flood over non-structure measures. The objective of this study is to develop superior real-time flood forecasting model by comparing the Neuro-fuzzy model and the multiple linear regression model. The Neuro-fuzzy model and the multiple linear regression model are established using same input data and applied for various flood events in Nakdong basin. The results show that the Neuro-fuzzy model can carry out flood forecasting results more accurately than the multiple linear regression model. This study can contribute to the establishment of a high accuracy flood information system that secure lead time in Nakdong basin.

Evaluation of applicability of pan coefficient estimation method by multiple linear regression analysis (다변량 선형회귀분석을 이용한 증발접시계수 산정방법 적용성 검토)

  • Rim, Chang-Soo
    • Journal of Korea Water Resources Association
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    • v.55 no.3
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    • pp.229-243
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    • 2022
  • The effects of monthly meteorological data measured at 11 stations in South Korea on pan coefficient were analyzed to develop the four types of multiple linear regression models for estimating pan coefficients. To evaluate the applicability of developed models, the models were compared with six previous models. Pan coefficients were most affected by air temperature for January, February, March, July, November and December, and by solar radiation for other months. On the whole, for 12 months of the year, the effects of wind speed and relative humidity on pan coefficient were less significant, compared with those of air temperature and solar radiation. For all meteorological stations and months, the model developed by applying 5 independent variables (wind speed, relative humidity, air temperature, ratio of sunshine duration and daylight duration, and solar radiation) for each station was the most effective for evaporation estimation. The model validation results indicate that the multiple linear regression models can be applied to some particular stations and months.

The health effects of low blood lead level in oxidative stress as a marker, serum gamma-glutamyl transpeptidase level, in male steelworkers

  • Su-Yeon Lee;Yong-Jin Lee;Young-Sun Min;Eun-Chul Jang;Soon-Chan Kwon;Inho Lee
    • Annals of Occupational and Environmental Medicine
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    • v.34
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    • pp.34.1-34.13
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    • 2022
  • Background: This study aimed to investigate the association between lead exposure and serum gamma-glutamyl transpeptidase (γGT) levels as an oxidative stress marker in male steelworkers. Methods: Data were collected during the annual health examination of workers in 2020. A total of 1,654 steelworkers were selected, and the variables for adjustment included the workers' general characteristics, lifestyle, and occupational characteristics. The association between the blood lead level (BLL) and serum γGT level was investigated by multiple linear and logistic regression analyses. The BLL and serum γGT values that were transformed into natural logarithms were used in multiple linear regression analysis, and the tertile of BLL was used in logistic regression analysis. Results: The geometric mean of the participants' BLLs and serum γGT level was 1.36 ㎍/dL and 27.72 IU/L, respectively. Their BLLs differed depending on age, body mass index (BMI), smoking status, drinking status, shift work, and working period, while their serum γGT levels differed depending on age, BMI, smoking status, drinking status, physical activity, and working period. In multiple linear regression analysis, the difference in models 1, 2, and 3 was significant, obtaining 0.326, 0.176, and 0.172 (all: p < 0.001), respectively. In the multiple linear regression analysis stratified according to drinking status, BMI, and age, BLLs were positively associated with serum γGT levels. Regarding the logistic regression analysis, the odds ratio of the third BLL tertile in models 1, 2, and 3 (for having an elevated serum γGT level within the first tertile reference) was 2.74, 1.83, and 1.81, respectively. Conclusions: BLL was positively associated with serum γGT levels in male steelworkers even at low lead concentrations (< 5 ㎍/dL).