• Title/Summary/Keyword: 역거리가중방법

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A Study on the Reviesd Methods of Missing Rainfall Data for Real-time Forecasting Systems (실시간 예보 시스템을 위한 우량자료 보정 기법 연구)

  • Han, Myoung-Sun;Kim, Chung-Soo;Kim, Hyoung-Seop;Kim, Hwi-Rin
    • Journal of Korea Water Resources Association
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    • v.42 no.2
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    • pp.131-139
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    • 2009
  • The weather accidents by global warming effect are increasing rapidly whole world. Flood forcasting system and hydrological database are operated by almost all the countries in the world. An objective of this study is to research revised methods of missing rainfall data and find more effective revised method for this operating system. 194 rainfall data of the Han river basin is used. Arithmetic average method, coefficient of correlation weighting method and inverse distance weighting method are compared to estimate revised methods. The result from the analysis shows that coefficient of correlation weighting method is best quantitatively among the 3 methods.

Analysis of Subway Adjacent Area Pedestrian Networks using Weighted Accessibility based on Road Slope (구배 기반 가중 접근성을 이용한 역세권 보행 네트워크 분석에 관한 연구)

  • Ha, Eun Ji;Jun, Chul Min
    • Spatial Information Research
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    • v.20 no.5
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    • pp.77-89
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    • 2012
  • Walking is the most basic personal mobility and its importance and concern is ever increasing with the highlighting of a new paradigm, such as transit oriented development, sustainable development and revitalization of green transport. The existing analytical research on pedestrian network is using a pedestrian's moving distance to a destination and integration in space syntax theory as its representative accessibility factors. However, the uniplanar network moving distance fails to reflect topographic characteristics, so the moving distance could show a similar result value in case of the regions for analysis that have a similar network structure to each other. Accordingly, the aim of this study is to suggest a new analytical methodology on pedestrian network accessibility in consideration of the grade in pedestrian sections and a pedestrian's size. this study, in its analysis of a uniplanar pedestrian network moving distance, analyzed the pedestrian network moving distance in consideration of the grade in pedestrian sections, and even the pedestrian network moving distance in consideration of a pedestrian's size, and suggested the methodology on pedestrian network accessibility analysis in consideration of a more substantive pedestrian's characteristics. It is hoped that the methodology used by this study will be used as the methodology on pedestrian network analysis which can reflect topographic characteristics in the pedestrian network analysis, and take a more substantive pedestrian's movement into account.

Estimation and Weighting of Sub-band Reliability for Multi-band Speech Recognition (다중대역 음성인식을 위한 부대역 신뢰도의 추정 및 가중)

  • 조훈영;지상문;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.6
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    • pp.552-558
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    • 2002
  • Recently, based on the human speech recognition (HSR) model of Fletcher, the multi-band speech recognition has been intensively studied by many researchers. As a new automatic speech recognition (ASR) technique, the multi-band speech recognition splits the frequency domain into several sub-bands and recognizes each sub-band independently. The likelihood scores of sub-bands are weighted according to reliabilities of sub-bands and re-combined to make a final decision. This approach is known to be robust under noisy environments. When the noise is stationary a sub-band SNR can be estimated using the noise information in non-speech interval. However, if the noise is non-stationary it is not feasible to obtain the sub-band SNR. This paper proposes the inverse sub-band distance (ISD) weighting, where a distance of each sub-band is calculated by a stochastic matching of input feature vectors and hidden Markov models. The inverse distance is used as a sub-band weight. Experiments on 1500∼1800㎐ band-limited white noise and classical guitar sound revealed that the proposed method could represent the sub-band reliability effectively and improve the performance under both stationary and non-stationary band-limited noise environments.

A Monte Carlo Comparison of the Small Sample Behavior of Disparity Measures

  • Hong, Jong-Seon;Jeong, Dong-Bin;Park, Yong-Seok
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.149-150
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    • 2003
  • 소표본 분할표 자료에서 적합도 검정통계량들의 카이제곱 근사 적용 가능에 대하여 많은 연구가 진행되었다. 소표본에서 세 가지 검정 통계량(피어슨 카이제곱 $X^{2}$, 일반화 가능도비 $G^{2}$, 그리고 역발산 I(2/3) 검정통계량)에 관하여 비교한 Rudas(1986)의 연구를 확장하여, 최근에 제안된 차이측도(BWHD(1/9), BWCS(1/3), NED(4/3) 검정통계량)를 포함시켜 비교 분석하였다. 독립모형의 이차원 분할표, 조건부 독립모형과 한 변수 독립 모형을 따르는 삼차원 분할표에 대한 모의실험을 통하여 생성된 90과 95 백분위수와 이에 대응하는 95% 신뢰구간을 살펴보고 실제 백분위수와 비교하였다. 그 결과 $X^{2}$, I(2/3), 그리고 BWHD(1/9) 검정통계량이 유사한 결과를 나타내었고 이 통계량들이 기존에 제안된 검정통계량들보다 적은 표본크기에서도 카이제곱 근사방법에 적용 가능함을 발견하였다.

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Comparison of Precipitation Distributions in Precipitation Data Sets Representing 1km Spatial Resolution over South Korea Produced by PRISM, IDW, and Cokriging (PRISM, 역거리가중법, 공동크리깅으로 작성한 1km 공간해상도의 남한 강수 자료에서 강수 분포의 비교)

  • Park, Jong-Chul;Kim, Man-Kyu
    • Journal of the Korean Association of Geographic Information Studies
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    • v.16 no.3
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    • pp.147-163
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    • 2013
  • The purpose of this study is to compare precipitation distributions in precipitation data sets over South Korea produced by three interpolation methods. The differences of precipitation caused by interpolation methods is an important information when the interpolated precipitation data sets were used in researches such as ecological and hydrological modeling as well as regional climate impact studies. In this study, the precipitation data sets were produced by IDW(Inverse Distance Weighting) and Cokriging in this study and the PRISM(Precipitation-elevation Regressions on Independent Slopes Model) data set obtained from Climate Change Information Center of Korea. The spatial resolution of the precipitation data is 1km. As a result, there was a great precipitation difference caused by interpolation methods in data of mountainous watersheds in general. Especially the difference of monthly precipitation was 10~20% or more in the mountainous watersheds near the Military Demarcation Line dividing North and South Korea, Mt. Sobaik, Mt. Worak, Mt. Deogyu, Mt. Jiri and Taeback Mountain Range. It means that a final result of a research can be affected by adopted interpolation method when an interpolated precipitation data set is used in the research for the these study sites.

A Proposal of an Interpolation Method of Missing Wind Velocity Data in Writing a Typical Weather Data (표준기상데이터 작성 시 누락된 풍속 데이터의 보간 방법 제안)

  • Park, So-Woo;Kim, Joo-wook;Song, Doo-sam
    • Journal of the Korean Solar Energy Society
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    • v.37 no.6
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    • pp.79-91
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    • 2017
  • The meteorological data of 1 hour interval are required to write a typical weather data for building energy simulation. However, many meterological data are missing and the interpolation method to recover the missing data is required. Especially, lots of meterological data are replicated by linear interpolation method because the changes are not significant. While, the wind velocity fluctuates with the time or locations, so linear interpolation method is not appropriate in interpolation of the wind velocity data. In this study, three interpolation methods, using surrounding wind velocity data, Inverse Distance Weighting (IDW), Revised Inverse Distance Weighting (IDW-r), were analyzed considering the characteristics of wind velocity. The Revised Inverse Distance Weighting method, proposed in this study, showed the highest reliability in restoration of the wind velocity data among the analyzed methods.

An Application of Statistical Downscaling Method for Construction of High-Resolution Coastal Wave Prediction System in East Sea (고해상도 동해 연안 파랑예측모델 구축을 위한 통계적 규모축소화 방법 적용)

  • Jee, Joon-Bum;Zo, Il-Sung;Lee, Kyu-Tae;Lee, Won-Hak
    • Journal of the Korean earth science society
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    • v.40 no.3
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    • pp.259-271
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    • 2019
  • A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.

Construction of Super-Resolution Convolutional Neural Network Model for Super-Resolution of Temperature Data (기온 데이터 초해상화를 위한 Super-Resolution Convolutional Neural Network 모델 구축)

  • Kim, Yong-Hoon;Im, Hyo-Hyuk;Ha, Ji-Hun;Park, Kun-Woo;Kim, Yong-Hyuk
    • Journal of the Korea Convergence Society
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    • v.11 no.8
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    • pp.7-13
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    • 2020
  • Meteorology and climate are closely related to human life. By using high-resolution weather data, services that are useful for real-life are available, and the need to produce high-resolution weather data is increasing. We propose a method for super-resolution temperature data using SRCNN. To evaluate the super-resolution temperature data, the temperature for a non-observation point is obtained by using the inverse distance weighting method, and the super-resolution temperature data using interpolation is compared with the super-resolution temperature data using SRCNN. We construct an SRCNN model suitable for super-resolution of temperature data and perform super-resolution of temperature data. As a result, the prediction performance of the super-resolution temperature data using SRCNN was about 10.8% higher than that using interpolation.

Comparison and Evaluation of Root Mean Square for Parameter Settings of Spatial Interpolation Method (공간보간법의 매개변수 설정에 따른 평균제곱근 비교 및 평가)

  • Lee, Hyung-Seok
    • Journal of the Korean Association of Geographic Information Studies
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    • v.13 no.3
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    • pp.29-41
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    • 2010
  • In this study, the prediction errors of various spatial interpolation methods used to model values at unmeasured locations was compared and the accuracy of these predictions was evaluated. The root mean square (RMS) was calculated by processing different parameters associated with spatial interpolation by using techniques such as inverse distance weighting, kriging, local polynomial interpolation and radial basis function to known elevation data of the east coastal area under the same condition. As a result, a circular model of simple kriging reached the smallest RMS value. Prediction map using the multiquadric method of a radial basis function was coincident with the spatial distribution obtained by constructing a triangulated irregular network of the study area through the raster mathematics. In addition, better interpolation results can be obtained by setting the optimal power value provided under the selected condition.

Collaborative Wideband Spectrum Sensing with Distance Based Weight Combining for Cognitive Radio System (인지무선 시스템을 위한 거리기반 가중결합을 이용한 협력 광대역 스펙트럼 센싱)

  • Lee, Mi-Sun;Kim, Yoon-Hyun;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.37-43
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    • 2012
  • In this paper, we analysis wideband spectrum sensing with distance based weight combining for Cognitive Radio (CR) systems. CR systems is implemented the spectrum of the Primary User(PU) by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of PU is BPSK signal and the wireless channel between a PU and CR systems is modeled as Gaussian channel. From the simulation results, the wideband sensing with distance based and Distance based weight Combing (DWC) methods shows higher spectrum sensing performance than single CR user spectrum sensing.