• Title/Summary/Keyword: Interval prediction

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Flood prediction in the Namgang Dam basin using a long short-term memory (LSTM) algorithm

  • Lee, Seungsoo;An, Hyunuk;Hur, Youngteck;Kim, Yeonsu;Byun, Jisun
    • Korean Journal of Agricultural Science
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    • v.47 no.3
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    • pp.471-483
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    • 2020
  • Flood prediction is an important issue to prevent damages by flood inundation caused by increasing high-intensity rainfall with climate change. In recent years, machine learning algorithms have been receiving attention in many scientific fields including hydrology, water resources, natural hazards, etc. The performance of a machine learning algorithm was investigated to predict the water elevation of a river in this study. The aim of this study was to develop a new method for securing a large enough lead time for flood defenses by predicting river water elevation using the a long- short-term memory (LSTM) technique. The water elevation data at the Oisong gauging station were selected to evaluate its applicability. The test data were the water elevation data measured by K-water from 15 February 2013 to 26 August 2018, approximately 5 years 6 months, at 1 hour intervals. To investigate the predictability of the data in terms of the data characteristics and the lead time of the prediction data, the data were divided into the same interval data (group-A) and time average data (group-B) set. Next, the predictability was evaluated by constructing a total of 36 cases. Based on the results, group-A had a more stable water elevation prediction skill compared to group-B with a lead time from 1 to 6 h. Thus, the LSTM technique using only measured water elevation data can be used for securing the appropriate lead time for flood defense in a river.

Accurate prediction of lane speeds by using neural network

  • Dong hyun Pyun;Changwoo Pyo
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.5
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    • pp.9-15
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    • 2023
  • In this paper, we propose a method predicting the speed of each lane from the link speed using a neural network. We took three measures for configuring learning data to increase prediction accuracy. The first one is to expand the spatial range of the data source by including 14 links connected to the beginning and end points of the link. We also increased the time interval from 07:00 to 22:00 and included the data generation time in the feature data. Finally, we marked weekdays and holidays. Results of experiments showed that the speed error was reduced by 21.9% from 6.4 km/h to 5.0 km/h for straight lane, by 12.9% from 8.5 km/h to 7.4 km/h for right turns, and by 5.7% from 8.7 km/h to 8.2 km/h for left-turns. As a secondary result, we confirmed that the prediction accuracy of each lane was high for city roads when the traffic flow was congested. The feature of the proposed method is that it predicts traffic conditions for each lane improving the accuracy of prediction.

Establishment of a Prediction Table of Parturition Day with Ultrasonography in Small Pet Dogs (소형 애완견에서 초음파 검사에 의한 분만일 예시표의 확립)

  • Oh, Ki-Seok;Kim, Bang-Sil;Park, Sang-Guk;Park, Chul-Ho;Kim, Jae-Hong;Mun, Byeong-Gwon;Kim, Hee-Su;Lee, Ju-Hwan;Park, In-Chul;Kim, Jong-Taek;Suh, Guk-Hyun;Son, Chang-Ho
    • Journal of Embryo Transfer
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    • v.23 no.3
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    • pp.155-160
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    • 2008
  • Serial ultrasonographic examinations were performed to establish a prediction table of parturition date in pregnant Maltese, Yorkshire Terrier, Shih-tzu and Miniature Schnauzer bitches. The inner chorionic cavity diameter and fetal head diameter in 45 pregnant bitches were converted retrospectively based on the day of parturition. The data of inner chorionic cavity diameter obtained from Day-44 to Day-25 and fetal head diameter obtained from Day-25 to Day-1 were used to compile a equations of prediction of parturition date. The 70 pregnant bitches with unknown mating time were examined to assess an accuracy of the equations established in this study. And these results were applied to the prediction of parturition date and compared to actual parturition date. The accuracy for parturition date within 0, $\pm$1, and $\pm$2 days interval using the equations of prediction of parturition date were 64.3%, 22.8% and 12.8%, respectively. The overall accuracy of prediction table of parturition day based on the ICCD and HD was 100% accurate within $\pm$2 days. Therefore, the prediction table seems to be a useful tool of the prediction of parturition day in practice.

Performance Prediction of Landing Gear Considering Uncertain Operating Parameters (운용 파라미터의 불확실성을 고려한 착륙장치 완충성능 해석)

  • Kim, Tae Uk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.7
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    • pp.921-927
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    • 2013
  • The performance estimation of a landing gear with uncertain parameters is presented. In actual use, many parameters can have certain degrees of variations that affect the energy absorbing performance. For example, the shock strut gas pressure, oil volume, tire pressure, and temperature can deviate from their nominal values. The objective function in this study is the ground reaction during touchdown, which is a function of the abovementioned parameters and time. To consider the uncertain properties, convex modeling and interval analysis are used to calculatethe objective function. The numerical results show that the ground reaction characteristics are quite different from those of the deterministic method. The peak load, which affects the efficiency and structural integrity, is increases considerably when the uncertainties are considered. Therefore, it is important to consider the uncertainties, and the proposed methodology can serve as an efficient method to estimate the effect of such uncertainties.

Investigating Optimal Aggregation Interval Size of Loop Detector Data for Travel Time Estimation and Predicition (통행시간 추정 및 예측을 위한 루프검지기 자료의 최적 집계간격 결정)

  • Yoo, So-Young;Rho, Jeong-Hyun;Park, Dong-Joo
    • Journal of Korean Society of Transportation
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    • v.22 no.6
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    • pp.109-120
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    • 2004
  • Since the late of 1990, there have been number of studies on the required number of probe vehicles and/or optimal aggregation interval sizes for travel time estimation and forecasting. However, in general one to five minutes are used as aggregation intervals for the travel time estimation intervals for the travel time estimation and/or forecasting of loop detector system without a reasonable validation. The objective of this study is to deveop models for identifying optimal aggregation interval sizes of loop detector data for travel time estimation and prediction. This study developed Cross Valiated Mean Square Error (CVMSE) model for the link and route travel time forecasting, The developed models were applied to the loop detector data of Kyeongbu expressway. It was found that the optimal aggregation sizes for the travel time estimation and forecasting are three to five minutes and ten to twenty minutes, respectively.

Adaptive Packet Transmission Interval for Massively Multiplayer Online First-Person Shooter Games

  • Seungmuk, Oh;Yoonsik, Shim
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.2
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    • pp.39-46
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    • 2023
  • We present an efficient packet transmission strategy for massively multiplayer online first-person shooter (MMOFPS) games using movement-adaptive packet transmission interval. The player motion in FPS games shows a wide spectrum of movement variability both in speed and orientation, where there is room for reducing the number of packets to be transmitted to the server depending on the predictability of the character's movement. In this work, the degree of variability (nonlinearity) of the player movements is measured at every packet transmission to calculate the next transmission time, which implements the adaptive transmission frequency according to the amount of movement change. Server-side prediction with a few auxiliary heuristics is performed in concert with the incoming packets to ensure reliability for synchronizing the connected clients. The comparison of our method with the previous fixed-interval transmission scheme is presented by demonstrating them using a test game environment.

Study on the Prediction of Turning Point of Typhoon Tracks using COMS Water Vapor Images (천리안 수증기 영상을 이용한 태풍진로의 전향위치 예측 연구)

  • Kim, Jong-Seok;Yoon, Ill-Hee
    • Journal of the Korean earth science society
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    • v.35 no.3
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    • pp.168-179
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    • 2014
  • The purpose of this study focuses on the prediction time and location of turning-point of typhoon tracks using the water vapor images of Communication, Ocean and Meteorological Satellite (COMS) which has a very short observation interval. It targets a more accurate prediction of turning-point of typhoon tracks through the relationship between dry slot and northern/southern oscillations of jet stream. Jet stream moves by the position of jet streak and the ${\upsilon}$-component velocity of geostrophic wind. If the ${\upsilon}$-component of geostrophic wind gets stronger toward south, jet stream develops into a circular jet. In that condition, dry slot in satellite water vapor imagery extends toward south, and typhoon track turns as the distance of curved moisture band (CMB) gets narrowed down. If the interval of CMB is below $15^{\circ}$ of latitude, the typhoon track is turning toward north or northeast within 24 hours. As a result, typhoon track showed that when dry slot position was located less than $32^{\circ}N$, typhoon turned its track at $20-23^{\circ}N$ ($1^{th}$ Kong-Rey 2007 and $17^{th}$ Jelawt at 2012), and when in $35^{\circ}N$ above, it turned at $27^{\circ}N$ ($4^{th}$ Man-yi 2007).

Assessment and Verification of Prediction Model(NIER('99)) for Road Traffic Noise in the Apartment Complex (아파트단지에서 국립환경과학원 도로교통소음 예측식('99)에 대한 통계학적 평가 및 검증)

  • Cho, Il-Hyoung;SunWoo, Young;Lee, Nae-Hyun
    • Journal of Korean Society of Environmental Engineers
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    • v.28 no.11
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    • pp.1198-1206
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    • 2006
  • We have carried out highway traffic noise prediction and measurement for 10 sites with representative road shapes and structures. A road traffic noise prediction model(NIER('99)) has been developed for environmental impact assessment in Korea. With the fitted regression analysis, the distribution ratio($R^2$) and Pearson correction coefficient(r) was 92.4% and 0.96 in $1^{st}$ floor, 38.7% and 0.66 in $3^{rd}$ floor, 42% and 0.65 in $5^{th}$ floor, 7.5% and 0.27 in $7^{th}$ floor, 28.4% and 0.53 in 10th floor, 35.6% and 0.60 in $13^{th}$ floor, 52.7% and 0.73 in $15^{th}$ floor, respectively. The measured values of the noise level except the 1st floor did not show a good agreement with the predicted noise level in the NIER('99) formula. Also, the NIER('99) formula demonstrated that the measured values weren't reasonably close to the predicted values, indicating the validity and adequacy of the predicted models with the fitted vs residual analysis in the 95% of confidence interval and 95% of predict interval. Using the equal variation on the basis of the residual vs fitted value, there was the significant difference for variation between $3^{rd}$ floor and $15^{th}$ floor except $1^{st}$ floor. The results suggested that the NIER('99) model obtained by the results according to the apartment floor must be improved and developed on the road traffic noise.

A Guideline for the Location of Bus Stop Type considering the Interval Distance of Bus Stops and Crosswalks at Mid-Block (Mid-Block상의 버스정류장과 횡단보도 이격거리를 고려한 버스정류장 배치형태 기준 연구)

  • Lee, Su-Beom;Gang, Tae-Uk;Gang, Dong-Su;Kim, Jang-Uk
    • Journal of Korean Society of Transportation
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    • v.28 no.2
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    • pp.123-133
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    • 2010
  • The national standards for the installation of pedestrian crosswalks prohibits installation of crosswalks within 200 meters of nearby overpasses, underpasses, or crosswalks. In case the exceptional installation is required, the feasibility study is to be thoroughly conducted by the local police agency. However, it is an undeniable fact that the specific installation standards for optimal types and locations of crosswalks are not yet to be established. This paper examines the development of traffic accident prediction model applicable to different types and locations of bus stops(type A and type B) at mid-block intersections. Furthermore, it develops the poisson regression model which sets the "number of traffic accidents" and "traffic accident severity" as dependent variables, while using "traffic volumes", "pedestrian traffic volumes" and "the distance between crosswalks and bus stops" as independent variables. According to the traffic accident prediction model applicable to the type A bus stop location, the traffic accident severity increases relative to the number of traffic volumes, the number of pedestrian traffic volumes, and the distance between crosswalks and bus stops. In case of the type B bus stop model, the further the bus stop is from crosswalks, the number of traffic accidents decreases while it increases when traffic volumes and pedestrian traffic volumes increase. Therefore, it is reasonable to state that the bus stop design which minimizes the traffic accidents is the type C design, which is the one in combination of type A and type B, and the optimal distance is found to be 65 meters. In case of the type A design and the type B design, the optimal distances are found to be within range 60~70meters.

Prediction Algorithm of Threshold Violation in Line Utilization using ARIMA model (ARIMA 모델을 이용한 설로 이용률의 임계값 위반 예측 기법)

  • 조강흥;조강홍;안성진;안성진;정진욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.8A
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    • pp.1153-1159
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    • 2000
  • This paper applies a seasonal ARIMA model to the timely forecasting in a line utilization and its confidence interval on the base of the past data of the lido utilization that QoS of the network is greatly influenced by and proposes the prediction algorithm of threshold violation in line utilization using the seasonal ARIMA model. We can predict the time of threshold violation in line utilization and provide the confidence based on probability. Also, we have evaluated the validity of the proposed model and estimated the value of a proper threshold and a detection probability, it thus appears that we have maximized the performance of this algorithm.

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