• Title/Summary/Keyword: 랜덤변수

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Comparative analysis of random forest on depression experiences of metropolitan and provincial residents (광역시·도민의 우울경험에 대한 Random Forest 비교분석)

  • Dong Su Lee;Yu Jeong Kim
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.07a
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    • pp.321-324
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    • 2023
  • 본 연구는 광역시와 광역도 간의 개인적 요인과 건강수준 정도가 우울경험 여부에 영향을 미치는 변수의 중요도를 파악하고자 시도되었다. 본 연구의 자료는 질병관리청의 2021년 지역사회건강조사 데이터를 활용하였다. 광역시의 데이터는 4,602건을 이용하였고, 광역도는 19,545건의 데이터를 이용하였다. 자료 분석에 활용된 빅데이터는 R 4.3.0 for Windows를 활용하여 단어 빈도 분석과 machine learning기법인 Random Forest분석을 실시하였다. 연구결과, train 데이터와 test 데이터의 과적합(overfitting)의 문제는 발생하지 않았으며, machine learning 기법의 분류모델은 약 94% 수준으로 나타났다. 분석 결과 광역시와 광역도 간의 우울경험여부에 미치는 중요도가 각각 다르게 나타났다. 두 지역의 시민에게 미치는 우울경험의 원인을 다르게 접근함으로써 보다 더 효율적인 정책수립이 가능 할 것으로 판단된다.

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A Study on Delivery Accuracy Using the Correlation between Errors (오차간의 상관관계를 이용하는 체계명중률 예측에 관한 연구)

  • Kim, Hyun Soo;Kim, Gunin;Kang, Hwan Il
    • The Journal of the Convergence on Culture Technology
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    • v.4 no.3
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    • pp.299-303
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    • 2018
  • Generally, when predicting the accuracy of the anti-air artillery system, the error is classified as fixed bias, variable bias, and random error. Then the standard deviation on the target is expressed as the square root of the squared sum of each error value which comes from the random error and variable bias and in the case of fixed bias, the mean value is shifted as the sum of errors from the fixed bias. At this time, the variables indicating the displacement of the direction of azimuth and elevation direction with regard to the change of the unit value of each error are weighted. These errors are then used to predict the system's delivery accuracy through a normally distributed integral. This paper presents a method of predicting system accuracy by considering the correlation of errors. This approach shows that it helps to predict the delivery accuracy of the system, precisely.

Comparing the Randomization Methods Considering the Covariates in a Clinical Trial (임상시험에서의 공변량을 고려한 확률화 방법들의 비교)

  • Yu, A-Mi;Lee, Jae-Won
    • The Korean Journal of Applied Statistics
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    • v.23 no.6
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    • pp.1047-1056
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    • 2010
  • In clinical trials, patients should be randomly allocated to treatment and control groups that consider the balance of their prognostic factors(covariates). There are many randomization methods and stratification is popular in Korea. In stratification, patients are divided into strata based on covariates and then the patients are randomly assigned to the arms of each strata. If the number of covariates increases then the number of strata increases rapidly and the results may not be reliable when the patients are inadequate in each strata. To complement this problem Pocock and Simon (1975) suggested a new randomization method that called for minimization focusing on the balance of covariates. In this study, we compare the advantages and disadvantages, the imbalance of covariates, the power of minimization, and other randomization methods by simulation.

Analysis of Horse Races: Prediction of Winning Horses in Horse Races Using Statistical Models (서울 경마 경기 우승마 예측 모형 연구)

  • Choe, Hyemin;Hwang, Nayoung;Hwang, Chankyoung;Song, Jongwoo
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1133-1146
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    • 2015
  • The Horse race industry has the largest proportion of the domestic legal gambling industry. However, there is limited statistical analysis on horse races versus other sports. We propose prediction models for winning horses in horse races using data mining techniques such as logistic regression, linear regression, and random forest. Horse races data are from the Korea Racing Authority and we use horse racing reports, information of racehorses, jockeys, and horse trainers. We consider two models based on ranks and time records. The analysis results show that prediction of ranks is affected by information on racehorses, number of wins of racehorses and jockeys. We place wagers for the last month of races based on our prediction models that produce serious profits.

Modeling of Train Radio Propagation Affected by Ground Reflected Wave in High-speed Railway (고속철도 지면반사파를 고려한 열차무선 전파모델)

  • Bae, Sung-Ho;Song, Ki-Hong;Choi, Kyu-Hyoung
    • Journal of the Korean Society for Railway
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    • v.16 no.6
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    • pp.460-465
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    • 2013
  • Radio propagation in a high-speed railway is affected by ground reflective waves that are due to irregular reflection by the railway track, which consists of rails, sleepers, and gravel. This paper provides a train radio propagation model that simulates an irregular track reflective wave as a random variable. A simulation study using the train radio propagation model shows that the path loss exponent is around 3.0, indicating a reduced path loss compared to the value of 4.0 in the general mobile radio environment. Regressive analysis of the received signal strength indicators measured in the Gyeongbu high-speed railway showed the results identical to those of the simulation. These results confirm the train radio propagation model and can be applied to the coverage estimation and the design of a train radio network.

Comparison Study of Performance Analysis Methods of Uplink NOMA Systems (상향링크 NOMA 시스템의 성능 해석 방법 비교 연구)

  • Kim, Nam-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.5
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    • pp.25-30
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    • 2020
  • Recently, non-orthogonal multiple access (NOMA) have been received considerable attention to be involved in the next generation mobile system. However, there are inherent inter-user interferences caused by the multiplexing multiple users in the same communication resource in NOMA systems. Two representative methods, the approximate white noise and random variable methods, have been adapted for the analysis of interferences in NOMA systems. In this paper, we derive the outage probabilities of an uplink NOMA system with the two analysis methods and compare the results. The numerical results of the outage probabilities versus transmitted power, distances, and power allocation are compared. We noticed that the derived functions are different each other, but the numerical results are coincident. It is shown that the two interference analysis methods can be applied to the analysis of NOMA systems.

Probabilistic Stability Analysis of Unsaturated Soil Slope under Rainfall Infiltration (강우침투에 대한 불포화 토사사면의 확률론적 안정해석)

  • Cho, Sung-Eun
    • Journal of the Korean Geotechnical Society
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    • v.34 no.5
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    • pp.37-51
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    • 2018
  • The slope failure due to the rainfall infiltration occurs frequently in Korea, since the depth of the weathered residual soil layer is shallow in mountainous region. Depth of the failure surface is shallow and tends to pass near the interface between impermeable bedrock and soil layer. Soil parameters that have a significant impact on the instability of unsaturated slopes due to rainfall infiltration inevitably include large uncertainties. Therefore, this study proposes a probabilistic analysis procedure by Monte Carlo Simulation which considers the hydraulic characteristics and strength characteristics of soil as random variables in order to predict slope failure due to rainfall infiltration. The Green-Ampt infiltration model was modified to reflect the boundary conditions on the slope surface according to the rainfall intensity and the boundary condition of the shallow impermeable bedrock was introduced to predict the stability of unsaturated soil slope with shallow bedrock under constant rainfall intensity. The results of infiltration analysis were used as inputs of infinite slope analysis to calculate the safety factor. The proposed analysis method can be used to calculate the time-dependent failure probability of soil slope due to rainfall infiltration.

Generation of a 3D Artificial Joint Surface and Characterization of Its Roughness (삼차원 인공 절리면의 생성과 이에 대한 거칠기 특성 평가)

  • Choi, Seung-Beum;Lee, Sudeuk;Jeon, Seokwon
    • Tunnel and Underground Space
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    • v.26 no.6
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    • pp.516-523
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    • 2016
  • Roughness of a joint surface is one of the most important parameters that affects the mechanical and hydraulic behavior of rock mass. Therefore, various studies on making constitutive model and/or roughness quantification have been conducted in experimental and empirical manners. Advances in recent 3D printing technology can be utilized to generate a joint surface with a specific roughness. In this study, a reliable technique to generate a rough joint surface was introduced and its quantitative assessment was made. Random midpoint displacement method was applied to generate a joint surface and the distribution of $Z_2$ was investigated to assess its roughness. As a result, a certain roughness can be embodied by controlling input parameters and furthermore it was able to generate a joint surface with specific roughness anisotropy.

Performance of cross-eye jamming due to amplitude mismatch: Comparison of performance analysis of angle tracking error (진폭비 불일치에 의한 cross-eye 재밍 성능: 각도 추적 오차 성능 분석 비교)

  • Kim, Je-An;Kim, Jin-Sung;Lee, Joon-Ho
    • Journal of Convergence for Information Technology
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    • v.11 no.11
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    • pp.51-56
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    • 2021
  • In this paper, performance degradation in the cross-eye jamming due to amplitude mismatch of two jamming antennas is considered. The mismatch of the amplitude ratio is modeled as a random variable with a normal distribution of the difference between the actual amplitude ratio and the nominal amplitude ratio due to mechanical defects. In the proposed analytic performance analysis, the first-order Taylor series expansion and the second-order Taylor series expansion is adopted. Performance measure of the cross-eye jamming is the mean square difference (MSD). The analytically derived MSD is validated by comparing the analytically derived MSD with the first-order Taylor series-based simulation-based MSD and the second-order Taylor series-based simulation-based MSD. It shows that the analysis-based MSD is superior to the Monte-Carlo-based MSD, which has a high calculation cost.

Development of Random Forest Model for Sewer-induced Sinkhole Susceptibility (손상 하수관으로 인한 지반함몰의 위험도 평가를 위한 랜덤 포레스트 모델 개발)

  • Kim, Joonyoung;Kang, Jae Mo;Baek, Sung-Ha
    • Journal of the Korean Geotechnical Society
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    • v.37 no.12
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    • pp.117-125
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    • 2021
  • The occurrence of ground subsidence and sinkhole in downtown areas, which threatens the safety of citizens, has been frequently reported. Among the various mechanisms of a sinkhole, soil erosion through the damaged part of the sewer pipe was found to be the main cause in Seoul. In this study, a random forest model for predicting the occurrence of sinkholes caused by damaged sewer pipes based on sewage pipe information was trained using the information on the sewage pipe and the locations of the sinkhole occurrence case in Seoul. The random forest model showed excellent performance in the prediction of sinkhole occurrence after the optimization of its hyperparameters. In addition, it was confirmed that the sewage pipe length, elevation above sea level, slope, depth of landfill, and the risk of ground subsidence were affected in the order of sewage pipe information used as input variables. The results of this study are expected to be used as basic data for the preparation of a sinkhole susceptibility map and the establishment of an underground cavity exploration plan and a sewage pipe maintenance plan.