• 제목/요약/키워드: coverage accuracy

검색결과 212건 처리시간 0.027초

Physics-informed neural network for 1D Saint-Venant Equations

  • Giang V. Nguyen;Xuan-Hien Le;Sungho Jung;Giha Lee
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2023년도 학술발표회
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    • pp.171-171
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    • 2023
  • This study investigates the capability of Physics-Informed Neural Networks (PINNs) for solving the solution of partial differential equations. Particularly, the 1D Saint-Venant Equations (SVEs) were considered, which describe the movement of water in a domain with shallow depth compared to its horizontal extent, and are widely adopted in hydrodynamics, river, and coastal engineering. The core contribution of this work is to combine the robustness of neural networks with the physical constraints of the SVEs. The PINNs method utilized a neural network to approximate the solutions of SVEs, while also enforcing the underlying physical principles of the equations. This allows for a more effective and reliable solution, especially in areas with complex geometry and varying bathymetry. To validate the robustness of the PINNs method, numerical experiments were conducted on several benchmark problems. The results show that the PINNs could be achieved high accuracy when compared with the solution from the numerical solution. Overall, this study demonstrates the potential of using PINNs and highlights the benefits of integrating neural network and physics information for improved efficiency and accuracy in solving SVEs.

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서해안 인접공항의 저고도 항공기상 정확도 연구 (A Study on Accuracy of Meteorological Information for Low Altitude Aerospace around the Airport on the West Coast)

  • 조영진;유광의
    • 한국항공운항학회지
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    • 제28권2호
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    • pp.53-62
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    • 2020
  • This study is to evaluate the accuracy of the meteorological information provided for the aircraft operating at low altitude. At first, it is necessary to identify crucial elements of weather information closely related to flight safety during low altitude flights. The study conducted a survey of pilots of low altitude aircraft, divided into pre-flight and in-flight phases, and reached an opinion that wind direction, wind speed, cloud coverage and ceiling and visibility are important items. Related to these items, we compared and calculated the accuracy of TAFs and METARs from Taean Airfield, Seosan Airport and Gunsan Airport because of their high number of domestic low-altitude flights. Accuracy analysis evaluated the accuracy of two numerical variables, Mean Absolute Error(MAE) and Root Mean Square Error(RMSE), and the cloud coverage which is categorical variable was calculated and compared by accuracy. For numeric variables, one-way ANOVA, which is a parameter-test, was approached to identify differences between actual forecast values and observations based on absolute errors for each item derived from the results of MAE and RMSE accuracy analyses. To determine the satisfaction of both normality assumptions and equivalence variability assumptions, the Shapiro-Wilk test was performed to verify that they do not have a normality distribution for numerical variables, and for the non-parametric test, Kruscal-Wallis test was conducted to determine whether or not they are satisfied.

A GPS-less Framework for Localization and Coverage Maintenance in Wireless Sensor Networks

  • Mahjri, Imen;Dhraief, Amine;Belghith, Abdelfettah;Drira, Khalil;Mathkour, Hassan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권1호
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    • pp.96-116
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    • 2016
  • Sensing coverage is a fundamental issue for Wireless Sensor Networks (WSNs). Several coverage configuration protocols have been developed; most of them presume the availability of precise knowledge about each node location via GPS receivers. However, equipping each sensor node with a GPS is very expensive in terms of both energy and cost. On the other hand, several GPS-less localization algorithms that aim at obtaining nodes locations with a low cost have been proposed. Although their deep correlation, sensing coverage and localization have long been treated separately. In this paper, we analyze, design and evaluate a novel integrated framework providing both localization and coverage guarantees for WSNs. We integrate the well-known Coverage Configuration Protocol CCP with an improved version of the localization algorithm AT-Dist. We enhanced the original specification of AT-Dist in order to guarantee the necessary localization accuracy required by CCP. In our proposed framework, a few number of nodes are assumed to know their exact positions and dynamically vary their transmission ranges. The remaining sensors positions are derived, as accurately as possible, using this little initial location information. All nodes positions (exact and derived) are then used as an input for the coverage module. Extensive simulation results show that, even with a very low anchor density, our proposal reaches the same performance and efficiency as the ideal CCP based on complete and precise knowledge of sensors coordinates.

인터넷 기반 iRTK 시스템 개발 (DEVELOPMENT OF iRTK (iNVERTED REAL-TIME KINEMATIC) SYSTEM BASED ON THE INTERNET)

  • 조정호;박종욱;최병규;박필호
    • Journal of Astronomy and Space Sciences
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    • 제20권3호
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    • pp.197-204
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    • 2003
  • iRTK 시스템을 개발하고 측위정확도 검증을 위해 중저가 수신기를 이용한 실험을 수행하였다. 각기 다른 네 가지 기선에 대해 iRTK 시스템을 이용한 측위실험이 이루어겼고, 1-3m수준의 측위정확도를 얻을 수 있었다. 제안하는 iRTK 기법은 기존의 RTK와 적용범위 및 정확도는 유사하지만, 중앙처리센터에서 일괄적으로 사용자의 위치를 계산하는 점이 다르며 유무선 인터넷을 이용하므로 통신범위에 제약을 받지 않는 장점이 있다. 그러나 유효응용범위가 5km미만인 단점도 있다. 따라서 향후 iRTK시스템의 효율적인 전국서비스에 대비한 보완책의 한 방안으로 VRS의 도입을 검토하였다.

Indirect structural health monitoring of a simplified laboratory-scale bridge model

  • Cerda, Fernando;Chen, Siheng;Bielak, Jacobo;Garrett, James H.;Rizzo, Piervincenzo;Kovacevic, Jelena
    • Smart Structures and Systems
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    • 제13권5호
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    • pp.849-868
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    • 2014
  • An indirect approach is explored for structural health bridge monitoring allowing for wide, yet cost-effective, bridge stock coverage. The detection capability of the approach is tested in a laboratory setting for three different reversible proxy types of damage scenarios: changes in the support conditions (rotational restraint), additional damping, and an added mass at the midspan. A set of frequency features is used in conjunction with a support vector machine classifier on data measured from a passing vehicle at the wheel and suspension levels, and directly from the bridge structure for comparison. For each type of damage, four levels of severity were explored. The results show that for each damage type, the classification accuracy based on data measured from the passing vehicle is, on average, as good as or better than the classification accuracy based on data measured from the bridge. Classification accuracy showed a steady trend for low (1-1.75 m/s) and high vehicle speeds (2-2.75 m/s), with a decrease of about 7% for the latter. These results show promise towards a highly mobile structural health bridge monitoring system for wide and cost-effective bridge stock coverage.

A Study on Obtaining Tree Data from Green Spaces in Parks Using Unmanned Aerial Vehicle Images: Focusing on Mureung Park in Chuncheon

  • Lee, Do-Hyung;Kil, Sung-Ho;Lee, Su-Been
    • 인간식물환경학회지
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    • 제24권4호
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    • pp.441-450
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    • 2021
  • Background and objective: The purpose of study is to analyze the three-dimensional (3D) structure by creating a 3D model for green spaces in a park using unmanned aerial vehicle (UAV) images. Methods: After producing a digital surface model (DSM) and a digital terrain model (DTM) using UAV images taken in Mureung Park in Chuncheon-si, we generated a digital tree height model (DHM). In addition, we used the mean shift algorithm to test the classification accuracy, and obtain accurate tree height and volume measures through field survey. Results: Most of the tree species planted in Mureung Park were Pinus koraiensis, followed by Pinus densiflora, and Zelkova serrata, and most of the shrubs planted were Rhododendron yedoense, followed by Buxus microphylla, and Spiraea prunifolia. The average height of trees measured at the site was 7.8 m, and the average height estimated by the model was 7.5 m, showing a difference of about 0.3 m. As a result of the t-test, there was no significant difference between height values of the field survey data and the model. The estimated green coverage and volume of the study site using the UAV were 5,019 m2 and 14,897 m3, respectively, and the green coverage and volume measured through the field survey were 6,339 m2 and 17,167 m3. It was analyzed that the green coverage showed a difference of about 21% and the volume showed a difference of about 13%. Conclusion: The UAV equipped with RTK (Real-Time Kinematic) and GNSS (Global Navigation Satellite System) modules used in this study could collect information on tree height, green coverage, and volume with relatively high accuracy within a short period of time. This could serve as an alternative to overcome the limitations of time and cost in previous field surveys using remote sensing techniques.

유·무인 항공영상을 이용한 심층학습 기반 녹피율 산정 (Derivation of Green Coverage Ratio Based on Deep Learning Using MAV and UAV Aerial Images)

  • 한승연;이임평
    • 대한원격탐사학회지
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    • 제37권6_1호
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    • pp.1757-1766
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    • 2021
  • 녹피율은 행정구역면적 대비 녹지가 피복된 면적의 비율로, 실질적인 도시녹화 지표로 활용되고 있다. 현재 녹피율은 토지피복지도를 기반하여 산출되는데, 토지피복지도의 낮은 공간해상도와 일정하지 않은 제작시기는 정확한 녹피율 산출과 정밀한 녹피분석을 어렵게 한다. 따라서 본 연구는 새로운 녹피율 산출방안으로 항공영상과 심층학습을 활용한 방안을 제안한다. 항공영상은 높은 해상도와 비교적 일정한 주기로 정밀한 분석을 가능하게 하며 심층 학습은 항공영상 내 녹지를 자동으로 탐지할 수 있다. 지자체는 매년 다양한 목적을 위해 유인항공영상을 취득하여 이를 활용해 신속하게 녹피율을 산출한다. 하지만 미리 취득된 유인항공영상은 취득 시기와 해상도, 센서와 같은 세부사항을 선택할 수 없어 정밀한 분석이 어려울 수 있다. 이러한 한계점은 다양한 센서의 탑재가 가능하고 낮은 고도의 비행으로 인해 고해상도 영상을 취득할 수 있는 무인항공기를 활용하여 보완될 수 있다. 이에 두 가지 항공영상으로부터 녹피율을 산출하였고 그 결과, 모든 녹지 유형으로 부터 높은 정확도로 녹피율을 산출할 수 있었다. 하지만 유인항공영상으로부터 산출된 녹피율은 복잡한 환경에서 한계가 있었다. 이를 보완하고자 활용한 무인항공영상은 복잡한 환경에서도 높은 정확도의 녹피율을 산출할 수 있었고 추가밴드 영상을 통해 더 정밀한 녹지 영역 탐지가 가능했다. 추후 기존 유인항공영상에 새로 취득한 무인항공영상을 보완적으로 사용해 녹피율을 효과적으로 산출할 수 있을 것이라 기대된다.

Extending Ionospheric Correction Coverage Area By Using A Neural Network Method

  • Kim, Mingyu;Kim, Jeongrae
    • International Journal of Aeronautical and Space Sciences
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    • 제17권1호
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    • pp.64-72
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    • 2016
  • The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.

극동 아시아에 있어서 DGPS 기준국들의 Coverage 예측에 관한 연구 (A study on Coverage-Prediction of the DGPS Stations in the Far East Asia)

  • 이회재;고광섭;정세모
    • 한국항해학회지
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    • 제24권5호
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    • pp.405-415
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    • 2000
  • DGPS/Radio beacons are currently being planned or installed in many countries. They offer a cost-effective way of distributing differential data to large number of users. These networks are also being deployed in South Korea, Japan, and China. Several DGPS stations among them are operating on the same frequencies. The DGPS signal based on a radio beacon in medium frequency band travels principally as a groundwave over the surface of the earth. The signal may also be received as skywaves at locations beyond about 100 km from the reference station. These skywaves interfere with groundwave signals due to fading. This factor has generally ignored in designing DGPS/Radio beacon systems. A further important factor is to reduce the coverage due to interference from other beacons on the same or adjacent frequencies. The desired signal may fade due to interaction between its skywave and groundwave components. It may degrade the accuracy of the positioning in a complex fashion. This paper estimates the coverage of Far East Asia DGPS stations which are operating on the same frequencies, which is based on the signal protection ratio and interference of the signal strength of the groundwave and skywave.

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NB-IoT 기술에서 Multiple Linear Regression Model을 활용하여 OTDOA 기반 포지셔닝 정확도 최적화 (Optimize OTDOA-based Positioning Accuracy by Utilizing Multiple Linear Regression Model under NB-IoT Technology)

  • 판이첸;김재수
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2020년도 제62차 하계학술대회논문집 28권2호
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    • pp.139-142
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    • 2020
  • NB-IoT(Narrow Band Internet of Things) is an emerging LPWAN(Low Power Wide Area Network) radio technology. NB-IoT has many advantages like low power, low cost, and high coverage. However low bandwidth and low sampling rates also lead to poor positioning accuracy. This paper proposed a solution to optimize positioning accuracy under the OTDOA(Observed Time Difference of Arrival) approach by utilizing MLR(Multiple Linear Regression) models. Through the MLR model to predict the influence degree of weather(temperature, humidity, light intensity and air pressure) on the arrival time of signal transmission to improve the measurement accuracy. The improvement of measurement accuracy can greatly improve IoT applications based on NB-IoT.

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