• Title/Summary/Keyword: 허용가능한 예측오차

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Estimation of the allowable range of prediction errors to determine the adequacy of groundwater level simulation results by an artificial intelligence model (인공지능 모델에 의한 지하수위 모의결과의 적절성 판단을 위한 허용가능한 예측오차 범위의 추정)

  • Shin, Mun-Ju;Moon, Soo-Hyoung;Moon, Duk-Chul;Ryu, Ho-Yoon;Kang, Kyung Goo
    • Journal of Korea Water Resources Association
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    • v.54 no.7
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    • pp.485-493
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    • 2021
  • Groundwater is an important water resource that can be used along with surface water. In particular, in the case of island regions, research on groundwater level variability is essential for stable groundwater use because the ratio of groundwater use is relatively high. Researches using artificial intelligence models (AIs) for the prediction and analysis of groundwater level variability are continuously increasing. However, there are insufficient studies presenting evaluation criteria to judge the appropriateness of groundwater level prediction. This study comprehensively analyzed the research results that predicted the groundwater level using AIs for various regions around the world over the past 20 years to present the range of allowable groundwater level prediction errors. As a result, the groundwater level prediction error increased as the observed groundwater level variability increased. Therefore, the criteria for evaluating the adequacy of the groundwater level prediction by an AI is presented as follows: less than or equal to the root mean square error or maximum error calculated using the linear regression equations presented in this study, or NSE ≥ 0.849 or R2 ≥ 0.880. This allowable prediction error range can be used as a reference for determining the appropriateness of the groundwater level prediction using an AI.

Proposal of allowable prediction error range for judging the adequacy of groundwater level simulation results of artificial intelligence models (인공지능 모델의 지하수위 모의결과 적절성 판단을 위한 허용가능 예측오차 범위 제안)

  • Shin, Mun-Ju;Ryu, Ho-Yoon;Kang, Su-Yeon;Lee, Jeong-Han;Kang, Kyung Goo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2022.05a
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    • pp.449-449
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    • 2022
  • 제주도는 용수의 대부분을 지하수에 의존하므로 지하수위의 예측 및 관리는 매우 중요한 사항이다. 제주도의 지층은 화산활동에 의한 현무암이 겹겹이 쌓여있는 형태를 나타내며 육지의 지층구조와 매우 다른 복잡한 형태를 나타낸다. 이에 따라 제주도 지하수위의 예측은 매우 난해하며, 최근에는 딥러닝 인공지능 모델을 활용하여 지하수위를 예측하는 연구사례가 증가하고 있다. 기존의 연구들은 인공지능 모델들이 지하수위를 적절히 예측한다고 보고하고 있으나 예측의 적절성에 대한 판단기준을 제시하지 못하였으므로 이에 대한 명확한 제시가 필요하다. 본 연구의 목표는 인공지능을 활용한 지하수위 예측오차가 허용 가능한지 판단할 수 있는 기준을 제시함에 있다. 이를 위해 전 세계의 과거 20년 동안 관련 연구결과들을 수집 및 분석하였으며, 분석 결과 인공지능 모델의 지하수위 예측오차는 지하수위 변동성이 큰 지역일수록 증가하는 것을 확인하였다. 이것은 지하수위의 변동형태가 크고 복잡할수록 인공지능 모델의 지하수위 예측성능은 낮아진다는 것을 의미한다. 이 관계를 명확하게 나타내기 위해 지하수위 최대변동폭과 평균제곱근오차 및 최대오차와의 관계를 선형회귀식으로 도출하여 허용가능한 예측오차 기준을 제시하였다. 그리고 기존 연구들에서 제시한 Nash-Sutcliffe 효율성지수와 결정계수를 분석하여 선형회귀식에 의한 기준을 보완할 수 있는 추가적인 기준을 제시하였다. 본 연구에서 제시한 인공지능 모델에 의한 지하수위 예측결과의 적절성 판단기준은 향후 지속적으로 증가하는 인공지능 예측연구에 유용하게 사용될 수 있다.

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Accuracy of soft tissue Profile change prediction in mandibular set-back surgery patients: a comparison of Quick Ceph Image $Pro^{TM}$ (ver 3.0) and $V-Ceph^{TM}$(ver 3.5) (하악골 후퇴 수술 환자의 연조직 측모 예측의 정확성: Quick Ceph Image $Pro^{TM}$(ver 3.0)와 $V-Ceph^{TM}$(Ver 3.5)의 비교)

  • Kim, Myoung-Kyun;Choi, Yong-Sung;Chung, Song-Woo;Jeon, Young-Mi;Kim, Jong-Ghee
    • The korean journal of orthodontics
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    • v.35 no.3 s.110
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    • pp.216-226
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    • 2005
  • The purpose of this study was to test and compare the accuracy and reliability of soft tissue profile predictions generated from two computer software programs (Quick Ceph Image $Pro^{TM}$ (ver 3.0) and $V-Ceph^{TM}$(ver 3.5)) for mandibular set-back surgery. The presurgical and postsurgical lateral cephalograms of 40 patients (20 males and 20 females) were traced on the same acetate paper with the reference taken as the cranial base outline. The presurgical skeletal outlines were digitized onto each computer program and the mandible was moved to mimic the expected surgical procedure with reverence to the mandibular anterior border and lower incisor position of the actual postsurgical skeletal outline. The soft tissue profile was generated and the amount and direction of skeletal movement was calculated with each software. The predicted soft tissue profile was compared to the actual postsurgical soft tissue profile. There were differences between the actual and the predicted surgical soft tissue profile charges in the magnitude and direction, especially the upper lip. lower lip and the soft tissue chin (P<0.05). Quick Ceph had more horizontal measurement errors and thickness errors for the upper lip and lower lip, but V-Ceph had more vertical measurement errors of the lower lip (P<0.05). There was a positive correlation between the prediction errors and the amount of mandibular movements in the vertical position of Sn, the horizontal position of Ls and the upper lip thickness for V-Ceph, and there was a negative correlation in the horizontal position and the thickness of the lower lip for Quick Ceph (P<0.05). However all of the Prediction errors of both imaging softwares were ranged within 3mm, and this was considered to be allowable clinically.

Validation of Real-Time River Flow Forecast Using AWS Rainfall Data (AWS 강우정보의 실시간 유량예측능력 평가)

  • Lee, Byong-Ju;Choi, Jae-Cheon;Choi, Young-Jean;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
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    • v.45 no.6
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    • pp.607-616
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    • 2012
  • The objective of this study is to evaluate the valid forecast lead time and the accuracy when AWS observed rainfall data are used for real-time river flow forecast. For this, Namhan river basin is selected as study area and SURF model is constructed during flood seasons in 2006~2009. The simulated flow with and without the assimilation of the observed flow data are well fitted. Effectiveness index (EI) is used to evaluate amount of improvement for the assimilation. EI at Chungju, Dalcheon, Hoengsung and Yeoju sites as evaluation points show 32.08%, 51.53%, 39.70% and 18.23% improved, respectively. In the results of the forecasted values using the limited observed rainfall data in each forecast time before peak flow occur, the peak flow under the 20% tolerance range of relative error at Chungju, Dalcheon, Hoengsung and Yeoju sites can be simulated in forecast time-11h, 2h, 3h and 5h and the flow volume in the same condition at those sites can be simulated in forecast time-13h, 2h, 4h and 9h, respectively. From this results, observed rainfall data can be used for real-time peak flow forecast because of basin lag time.

The Construction of 3D Spatial Imagery Information of Dam reservoir using LiDAR and Multi Beam Echo Sounder (LiDAR와 MBES를 이용한 댐 저수지 3차원 공간영상정보 구축)

  • Lee, Geun-Sang;Choi, Yun-Woong
    • Spatial Information Research
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    • v.18 no.3
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    • pp.1-11
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    • 2010
  • Recently, the construction of three dimensional spatial information of Dam reservoir area is very important part in Dam management work such as sediment survey, but it is difficult to acquire detailed terrain data because totalstation and single beam echo sounder are applied to terrain survey. This study presented method to construct detailed terrain data of Dam reservoir area using LiDAR and multi beam echo sounder. First, LiDAR survey was carried out in land zone and calibration process was applied by ground control point. And also the DEM of land zone was constructed by using algorithm, which eliminated building and vegetation class. As the result of validation of LiDAR DEM using GPS terrain survey, it was possible to construct three dimensional terrain data that was satisfied with the tolerance error of LiDAR, which was the standard error of LiDAR DEM showed as 0.108m. Also multi beam echo sounder was applied to the survey of water zone and it could construct spatial information that was satisfied with bathymetry surveying tolerance error of International Hydrographic Organization by validation with terrain survey data. And LiDAR and multi beam echo sounder data were integrated and it was possible to construct three dimensional spatial imagery information that can be applied to Dam management work such as the estimation of sediment amounts or the monitoring of terrain change by linking with high resolution orthophoto.

Development and Validation of Predictive Models of Esherichia coli O157:H7 Growth in Paprika (파프리카에서 병원성 대장균의 성장예측 모델 개발 및 검증)

  • Yun, Hyejeong;Kim, Juhui;Park, Kyeonghun;Ryu, Kyoung-Yul;Kim, Byung Seok
    • Journal of Food Hygiene and Safety
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    • v.28 no.2
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    • pp.168-173
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    • 2013
  • This study was carried out to develop and validate predictive models of E. coli O157:H7 growth. Growth data of E. coli O157:H7 in Paprika were collected at 12, 24, 30 and $36^{\circ}C$. The population increased into 3.0 to 3.8 log10 CFU/g within 4 days, then continued to increase at a slower rate through 10 days of storage at $12^{\circ}C$. The lag time (LT) and maximum specific growth rate (SGR) obtained from each primary model was then modeled as a function of temperature using Davey and square root equations, respectively. For interpolation of performance evaluation, growth data for a mixture of E. coli O157:H7 were collected at time intervals in paprika incubated at the different temperatures, which was not used in model development. Results of model performance for interpolation data demonstrated that induced secondary models showed acceptable goodness of fit. Relative errors in the LT and SGR model for interpolation data (18 and $27^{\circ}C$) was 100%, which show acceptable goodness of fit and validated for interpolation. The primary and secondary models developed in this study can be used to establish tertiary models to quantify the effects of temperature on the growth of E. coli O157:H7 in paprika.

Development and Validation of the Stand Density Management Diagram for Pinus densiflora Forests in Korea (소나무 임분밀도관리도 작성 및 실용성 검정)

  • Park, Joon Hyung;Lee, Kwang Soo;Yoo, Byung Oh;Park, Yong Bae;Jung, Su Young
    • Journal of Korean Society of Forest Science
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    • v.105 no.3
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    • pp.342-350
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    • 2016
  • This study aims to make the stand density management diagram which is very useful for establishing systematic management plan and obtaining management goal in Pinus densiflora forest. To estimate 5 models mainly composed of stand density management diagram, we used total of 1,886 sample plots having more than 75% of the total basal area of the pine trees in each stand. To test the goodness of fit, $X^2$ was computed with a significance level of 5%, and the acceptable error range as 20%. Also standard deviation of the model was $34.59m^3{\cdot}ha^{-1}$, minimum acceptable error range was 16.59% and coefficient of variation was 22.11%. If we use the stand density management diagram, it would be useful to establish the timber yield and thinning plan understanding the pathway of stand density management.

An evaluation of wall functions for RANS computation of turbulent flows (난류 흐름의 RANS 수치모의를 위한 벽함수 성능 평가)

  • Yoo, Donggeun;Paik, Joongcheol
    • Journal of Korea Water Resources Association
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    • v.53 no.1
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    • pp.1-13
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    • 2020
  • The most common approach for computing engineering flow problems at high Reynolds number is still the Reynolds-averaged Navier-Stokes (RANS) computations based on turbulence models with wall functions. The recently developed generalized wall functions blending between the wall-limiting viscous and the outer logarithmic relations ensure a smooth transition of flow quantities across two regions. The performances and convergence properties of widely used turbulence models with wall functions that are applicable for turbulence kinetic energy (TKE), turbulent and specific dissipation rates, and eddy viscosity are presented through a series of near wall flow simulations. The present results show that RNG k-𝜖 model should be carefully applied with small tolerance to get the stable solution when the first grid lies in the buffer layer. The standard k-𝜖 and RNG k-𝜖 models are not sensitive to the selection of wall functions for both TKE and eddy viscosity, while the k-ω SST model should be applied together with kL-wall function for TKE and nutUB-wall functions for eddy viscosity to ensure accurate and stable boundary conditions. The applications to a backward-facing step flow at Re=155,000 reveal that the reattachment length is reasonably well predicted on appropriately refined mesh by all turbulence models, except the standard k-𝜖 model which about 13% underestimates the reattachment length regardless of the grid refinement.

A Study on the Architecture Modeling of Information System using Simulation (시뮬레이션을 이용한 정보시스템 아키텍쳐 모델링에 관한 연구)

  • Park, Sang-Kook;Kim, Jong-Bae
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.10a
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    • pp.455-458
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    • 2013
  • The conventional design of the information system architecture based on the personal experience of information systems has been acted as a limit in progress utilizing appropriate resource allocation and performance improvements. Architecture design depending on personal experience makes differences in variance of a designer's experience, intellectual level in related tasks and surroundings, and architecture quality according to individual's propensity. After all these problems cause a waste of expensive hardware resources. At working place, post-monitoring tools are diversely developed and are running to find the bottleneck and the process problems in the information operation. However, there are no simulation tools or models that are used for expecting and counteracting the problems at early period of designing architecture. To solve these problems we will first develop a simulation model for designing information system architecture in a pilot form, and will verify validity. If an error rate is found in the permissible range, then it can be said that the simulation reflects the characteristic of information system architecture. After the model is developed in a level that can be used in various ways, more accurate performance computation will be able to do, getting out of the old way relying on calculations, and prevent the existence of idle resources and expense waste that comes from the wrong design of architecture.

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Statistical Analysis of Receding Horizon Particle Swarm Optimization for Multi-Robot Formation Control (다개체 로봇 편대 제어를 위한 이동 구간 입자 군집 최적화 알고리즘의 통계적 성능 분석)

  • Lee, Seung-Mok
    • Journal of Korea Society of Industrial Information Systems
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    • v.24 no.5
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    • pp.115-120
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    • 2019
  • In this paper, we present the results of the performance statistical analysis of the multi-robot formation control based on receding horizon particle swarm optimization (RHPSO). The formation control problem of multi-robot system can be defined as a constrained nonlinear optimization problem when considering collision avoidance between robots. In general, the constrained nonlinear optimization problem has a problem that it takes a long time to find the optimal solution. The RHPSO algorithm was proposed to quickly find a suboptimal solution to the optimization problem of multi-robot formation control. The computational complexity of the RHPSO increases as the number of candidate solutions and generations increases. Therefore, it is important to find a suboptimal solution that can be used for real-time control with minimal candidate solutions and generations. In this paper, we compared the formation error according to the number of candidate solutions and the number of generations. Through numerical simulations under various conditions, the results are analyzed statistically and the minimum number of candidate solutions and the minimum number of generations of the RHPSO algorithm are derived within the allowable control error.