• Title/Summary/Keyword: Case Prediction

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Prediction of Highway Traffic Noise-calculation of Sound Attenuation during Propagation (고속도로 교통소음 예측-전달감쇠 산정)

  • 조대승;김진형;최태묵;오정한;김성훈
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.3
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    • pp.236-242
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    • 2002
  • This paper presents some advanced and supplemental methods to enhance the accuracy In case of calculating geometric divergence attenuation, attenuation by multiple screening structures, ground attenuation at unflat surfaces of sound during propagation outdoors by the methods specified in ISO 9613-2. Moreover, a calculation method for considering short-term wind effect, specified in ASJ Model-1998, is also introduced. To verity the accuracy of adopted methods, we have carried out highway traffic noise prediction and measurement at tile twelve locations appearing representative road shapes and structures, such as flat, retained cut, elevated, barrier-constructed roads. From the results, we have confirmed the predicted results show good correspondence with the measured at direct, diffracted and reflected sound fields within 30 m from the center of near side lane.

Numerical and Experimental Study on Spray Atomization Characteristics of GDI Injector (직접 분사식 가솔린 기관 인젝터의 분무 미립화 특성에 대한 해석 및 실험적 연구)

  • Lee, C.S.;Rhyu, Y.;Kim, H.J.;Park, S.W.
    • Journal of ILASS-Korea
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    • v.7 no.3
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    • pp.1-6
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    • 2002
  • In this study numerical and experimental study on the spray atomization characteristics of a GDI injector is performed. To carry out numerical analysis, four hybrid models that are composed of conical sheet disintegration model, LISA model, DDB model, and RT model are used. The experimental results to evaluate the prediction accuracy of hybrid models are obtained by using phase Doppler particle analyzer and spray visualization system. It is shown that the prediction accuracy of hybrid model concerning spray developing process and spray tip penetration is good for all hybrid models, but the hybrid breakup models show different prediction of accuracy in the case of local radial SMD distribution.

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A Study on the Development of the Train Wind Rate Prediction Program in Tunnel of the Subway (지하철 터널내 열차풍 예측 프로그램 개발에 관한 연구)

  • Kim, J.R.;Choi, K.H.
    • Journal of Power System Engineering
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    • v.3 no.1
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    • pp.38-44
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    • 1999
  • Subway is one of the most important transportation and its facilities are increased by the drift of population to cities in these days. But heat generation results from lighting, human and traffic increase in subway, half-closed space, gives uncomfortable sense to the subway passengers. Therefore, natural ventilation by piston effect is done to relieve uncomfortable sense. But train wind by piston effect gives uncomfortable sense to the subway passengers, too. So the numerical calculation of inflow and outflow amounts is important to predict thermal environment and reduce train wind. In case of actual survey of train wind in target station, the amount of train wind are about $3100m^3/train$ at the minimum, about $6000m^3/train$ at the maximum, about $4200m^3/train$ on average. When comparison between simulation for train wind prediction and actual survey for accuracy was done train wind prediction program showed similar results.

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A Prediction Method Combining Clustering Method and Stepwise Regression (군집분석 기법과 단계별 회귀모델을 결합한 예측 방법)

  • Chong Il-gyo;Jun Chi-Hyuck
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.949-952
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    • 2002
  • A regression model is used in predicting the response variable given predictor variables However, in case of large number of predictor variables, a regression model has some problems such as multicollinearity, interpretation of the functional relationship between the response and predictors and prediction accuracy. A clustering method and stepwise regression could be used to reduce the amount of data by grouping predictors having similar properties and by selecting the subset of predictors. respectively. This paper proposes a prediction method combining clustering method and stepwise regression. The proposed method fits a global model and local models and predicts responses given new observations by using both models. The paper also compares the performance of proposed method with stepwise regression via a real data of ample obtained in a steel process.

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A Study on Lateral Bearing Capacity of PHC Piles Driven Vertically in Decomposed Granite and Clayey Soil (화강토와 점토지반에 연직으로 타입된 PHC말뚝의 수평지지력에 관한 연구(지반공학))

  • 문영민;이문수;이대재
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2000.10a
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    • pp.466-470
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    • 2000
  • Recently, the calculation of horizontal bearing capacity of piles foundation has been considered very important for earthquake or wind resistant design in Korea. This study deals with the lateral resistance of PHC pile instead of vertical capacity for earthquake resistant design as well as wind. As case study, the prediction values were compared with measured ones based on ASTM. During this research, Matlock & Reese, Davisson & Gill, Broms and Chang's methods were selected in calculating prediction of lateral resistance of PHC piles. In decomposed granite and clayey soils, The result showed that prediction values proposed by Matlock & Reese(Davisson & Gill), Chang and Broms were smaller values than real values. four proposed methods by Matlock & Reese(Davisson & Gill) and Chang based on lateral deflection and Broms by ultimate lateral resistance turned out valid in view of engineering practice.

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A Prediction Method for Sabot-Trajectory of Projectile by using High Speed Camera Data Analysis (고속카메라 데이터 분석을 통한 발사체 지지대 분산 궤적의 근사적 예측 방법)

  • Park, Yunho;Woo, Hokil
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.1
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    • pp.1-9
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    • 2018
  • In this paper, we have proposed a prediction method for sabot-trajectory of projectile using high speed camera data analysis. Through analyzing trajectory of sabot with high speed camera data, we can extract its real velocity and acceleration including effects of friction force, pressure of flume, etc. Using these data, we suggest a prediction method for sabot-trajectory of projectile having variable acceleration, especially for minimum and maximum acceleration, by using interpolation method for velocity and acceleration data of sabot. Also we perform the projectile launching tests to achieve the trajectory of sabot in case of minimum and maximum thrust. Simulation results show that they are similar to real tests data, for example velocity, acceleration and the trajectory of sabot.

A Study on the Prediction of Train Noise Propagation Using the Spark Discharge Sound Source (스파크음원을 이용한 철도소음 전파예측에 관한 기초적 연구)

  • Joo Jin-Soo;Kim Jae-Chul
    • Proceedings of the KSR Conference
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    • 2003.10c
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    • pp.132-137
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    • 2003
  • This paper concerns the prediction of railway noise propagation using scale model experiment in acoustics. In order to make acoustical experiment the digital signal processing technique are applied and spark discharge sound sources have been developed in which impulse response measured in 1/20 scale model railway. In the case of scale model experiment, it is difficult to realize sufficiently small size and directivity and to get sufficient sound energy and to get repeatability. Several type of Spark discharge sound source is made in laboratory. Experiment results are compared with the calculated results by the prediction model. As the results, it was found that railway noise could be predicted in acoustical scale model experiment using spark discharge sound source.

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THE PREDICTION OF FLARE PRODUCTION USING SOLAR ACTIVITY DATA (태양활동 자료를 이용한 플레어 발생 예보)

  • Lee, Jin-Lee;Kim, Gap-Seong
    • Publications of The Korean Astronomical Society
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    • v.11 no.1
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    • pp.263-277
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    • 1996
  • We have intensively carried out numerical calculations on flare predictions from the solar activity data for photospheric sunspots, chromospheric flare and plages, coronal X-ray intensities and 2800MHz radio fluxes, by using multilinear regression method. Intensities of solar flares for the next day have been predicted from the solar data between 1977-1982 and 1993-1996. Firstly, we have calculated flare predictions with the multilinear regression method, by using separate solar data in growth and decay phase of sunspot area and magnetic field strength from the whole data on solar activities. Secondly, the same operations as above have been made for the remaining data after removal of the data with large deviation from the mean calculated by the above prediction method. we have reached a conclusion that average hit ratio of correct predictions to total predictions of flares with class of M5 over has been as high as 70% for the first case and that of correct prediction number to total observation number has been shown as 61%.

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A Study on the Scheme of the Mobility Prediction for Guaranting Handoff QoS in Wireless Networks (무선 통신망에서 Handoff QoS 보장을 위한 이동성 예측 기법에 관한 연구)

  • Lee, Hyeon-Uk;Kwon, Tea-Wook
    • 한국정보통신설비학회:학술대회논문집
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    • 2008.08a
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    • pp.447-453
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    • 2008
  • It is decidedly important to ensure QoS(Quality of Service) in order to make it possible a variety of multi-media services and realtime contents services in Wireless networks. One of methods to offer these services is the advanced prediction of Handoff through terminal's directional. In this paper, it is applied that the AP weight for the ground information of peripheral cell and the weight value of history table for the cell frequently visited. Also, it is expected that will be guarant QoS of substantial data in the case of Handoff through exact directional prediction of the next cell by using Kalman Filter algorithm applied GPS coordinates value.

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PREDICTION OF U.S. GOLD FUTURES PRICES USING WAVELET ANALYSIS; A STUDY ON DEEP LEARNING MODELS

  • LEE, Donghui;KIM, Donghyun;YOON, Ji-Hun
    • Journal of applied mathematics & informatics
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    • v.39 no.1_2
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    • pp.239-249
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    • 2021
  • This study attempts to predict the price of gold futures, a real financial product, using ARIMA and LSTM. The wavelet analysis was applied to the data to predict the price of gold futures through LSTM and ARIMA. As results, it is confirmed that the prediction performance of the existing model of predict was improved. the case of predict of price of gold futures, we confirmed that the use of a deep learning model that is not affected by the non-stationary series data is suitable and the possibility of improving the accuracy of prediction through wavelet analysis.