• Title/Summary/Keyword: 다항회귀모형

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Adaptation and Implementation of Polynomial Regression Function for Estimating Moving Object's Trajectory (이동객체의 경로 추정을 위한 다항회귀함수 적용 및 구현)

  • Yang, Eun-Joo;Jung, Young-Jin;Jang, Seong-Youn;Ahn, Yoon-Ae;Ryu, Keun-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.109-112
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    • 2001
  • 실세계의 움직이는 여러 이동객체들은 시공간적인 특성을 지니고 있다. 이들 객체는 실세계의 공간 즉, 점들의 집합 내에 위치해 있으며 이들을 데이터베이스로 표현 및 관리하기 위해서는 점 흑은 영역 형태로 표현하고 저장하게 된다. 이 논문에서는 샘플링되지 않은 시점에 대한 이동객체의 위치 질의시 발생할 수 있는 이동객체의 불확실성을 처리하는 데 있어서, 기존의 선형 보간법 대신 이동객체의 위치값 자체의 오차범위까지 고려하는 다항회함수(polynomial regression function)을 이용한 이동객체의 불확실한 이동위치 추정 방법을 제시하였으며, 이동객체의 이동경로를 구현하였다. 다항회귀모형을 이용할 경우 선형 보간법 보다 추정된 위치간에 대한 오차를 줄일 수 있으며, 이동객체의 과거 및 미래 위치값을 사용자에게 반환해 줄 수 있는 장점을 가진다.

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D-optimal design in polynomial spline regression (다항 스플라인 회귀모형에서의 D-최적실험계획)

  • 임용빈
    • The Korean Journal of Applied Statistics
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    • v.4 no.2
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    • pp.171-178
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    • 1991
  • For the polynomial spline regression with fixed knots, some properties of the D-optimal design are discussed. Also the D-optimal design for some cases are found analytically by using a normalized B-spline basis for $S(P_m : k : \Delta)$. Based on the Kiefer-Wolfowitz equivalence theorem, the D-optimal design for some cases are found by numerical methods.

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Prediction of fine dust PM10 using a deep neural network model (심층 신경망모형을 사용한 미세먼지 PM10의 예측)

  • Jeon, Seonghyeon;Son, Young Sook
    • The Korean Journal of Applied Statistics
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    • v.31 no.2
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    • pp.265-285
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    • 2018
  • In this study, we applied a deep neural network model to predict four grades of fine dust $PM_{10}$, 'Good, Moderate, Bad, Very Bad' and two grades, 'Good or Moderate and Bad or Very Bad'. The deep neural network model and existing classification techniques (such as neural network model, multinomial logistic regression model, support vector machine, and random forest) were applied to fine dust daily data observed from 2010 to 2015 in six major metropolitan areas of Korea. Data analysis shows that the deep neural network model outperforms others in the sense of accuracy.

Logistic Regressions with Sensory Evaluation Data about Hanwoo Steer Beef (한우 거세우 고기 관능평가 데이터의 로지스틱 회귀분석)

  • Lee, Hye-Jung;Kim, Jae-Hee
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.857-870
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    • 2010
  • This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

Rainfall Adjustment on Duration and Topographic Elevation (지속시간 및 표고에 따른 강우량 보정에 관한 연구)

  • Um, Myoung-Jin;Cho, Won-Cheol;Rim, Hae-Wook
    • Journal of Korea Water Resources Association
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    • v.40 no.7
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    • pp.511-521
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    • 2007
  • The objective of this study is to develop a method of rainfall adjustment on duration and topographic elevation for rainfall data in Jejudo. The method of rainfall adjustment is based on the polynomial regression analysis for the hourly rainfall data and the distribution of observatories of korea meteorological administration. As the results of modeling have shown, duration and rainfall are more correlated than topographic elevation and rainfall, and the model which considers only an elevation exaggerates the amount of rainfall adjustment. Hence the model of duration-elevation-rainfall is more competitive to the natural rainfall event than the model of topographic elevation-rainfall. However this model require to supplement a small number of rainfall observatories and short observed period.

A Study on the Application of Suitable Urban Regeneration Project Types Reflecting the Spatial Characteristics of Urban Declining Areas (도시 쇠퇴지역 공간 특성을 반영한 적합 도시재생 사업유형 적용방안 연구)

  • CHO, Don-Cherl;SHIN, Dong-Bin
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.4
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    • pp.148-163
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    • 2021
  • The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

A comparison of models for the quantal response on tumor incidence data in mixture experiments (계수적 반응을 갖는 종양 억제 혼합물 실험에서 모형 비교)

  • Kim, Jung Il
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.5
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    • pp.1021-1026
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    • 2017
  • Mixture experiments are commonly encountered in many fields including food, chemical and pharmaceutical industries. In mixture experiments, measured response depends on the proportions of the components present in the mixture and not on the amount of the mixture. Statistical analysis of the data from mixture experiments has mainly focused on a continuous response variable. In the example of quantal response data in mixture experiments, however, the tumor incidence data have been analyzed in Chen et al. (1996) to study the effects of 3 dietary components on the expression of mammary gland tumor. In this paper, we compared the logistic regression models with linear predictors such as second degree Scheffe polynomial model, Becker model and Akay model in terms of classification accuracy.

Development of a Short-term Rainfall Forecast Model Using Sequential CAPPI Data (연속 CAPPI 자료를 이용한 단기강우예측모형 개발)

  • Kim, Gwangseob;Kim, Jong Pil
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.6B
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    • pp.543-550
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    • 2009
  • The traditional simple extrapolation type short term quantitative rainfall forecast can not realize the evolution of rainfall generating weather system. To overcome the drawback of the linear extrapolation type rainfall forecasting model, the history of a weather system from sequential weather radar information and a polynomial regression technique were used to generate forecast fileds of x-directional, y-directional velocities and radar reflectivity which considered the nonlinear behavior related to the evolution of weather systems. Results demonstrated that test statistics of forecasts using the developed model is better than that of 2-CAPPI forecast. However there is still a large room to improve the forecast of spatial and temporal evolution of local storms since the model is not based on a fully physical approach but a statistical approach.

A Study on the Area Load Forecasting Algorithm for the Transmission Planning (송변전 계획을 위한 지구별 수요예측 산법에 관한 연구)

  • Kim, Jin-Ki;Hwang, Kab-Ju
    • Proceedings of the KIEE Conference
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    • 1999.07c
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    • pp.1108-1110
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    • 1999
  • 본 연구를 통하여 전력계통의 송변전 계획에 필요한 장기 지구별 수요예측 산법을 제안하였다. 소규모 지구의 수요예측을 위한 중회귀 모형 도입시 단순한 다항식 회귀모형만으로는 장기예측을 하는데 한계가 있으므로 다항회귀 과정을 변형하거나, 새로운 기능을 보완하여 예측정확도를 높이려는 시도가 수행 되어왔다. 본 논문에서는 장기 예측시 나타나는 미래의 예측 수요의 과도한 변화를 감소시켜 예측 정확도를 개선할 수 있는 수평년도수요를 도입하였으며, 종래 추세 분석에서 난점으로 지적되어 온 변전소의 신설 및 폐지에 따른 수요이전으로 야기되는 예측의 불안정성을 개선하였다. 제안한 산법을 검증하기 위하여 우리나라 실계통에 적용하였다.

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A Study for the Development of Motion Picture Box-office Prediction Model (영화 흥행 결정 요인과 흥행 성과 예측 연구)

  • Kim, Yon-Hyong;Hong, Jeong-Han
    • Communications for Statistical Applications and Methods
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    • v.18 no.6
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    • pp.859-869
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    • 2011
  • Interest has increased in academic research regarding key factors that drive box-office success as well as the ability to predict the box-office success of a movie from a commercial perspective. This study analyzed the relationship between key success factors of a movie and box office records based on movies released in 2010 in Korea. At the pre-production investment decision-making stage, the movie genre, motion picture rating, director power, and actor power were statistically significant. At the stage of distribution decision-making process after movie production, among other factors, the influence of star actors, number of screens, power of distributors, and social media turned out to be statistically significant. We verified movie success factors through the application of a Multinomial Logit Model that used the concept of choice probabilities. The Multinomial Logit Model resulted in a higher level of accuracy in predicting box-office success compared to the Artificial Neural Network and Discriminant Analysis.