• Title/Summary/Keyword: inverse distance method

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Optimal distance exponent of inverse distance method (역거리법의 최적 거리 지수)

  • Yoo, Ju-Hwan
    • Journal of Korea Water Resources Association
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    • v.51 no.5
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    • pp.451-459
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    • 2018
  • We calculated the optimal exponent values based on the hourly rainfall data observed in South Korea by treating the exponent value as a variable without fixing it as a square in the inverse distance method. For this purpose, rainfall observation stations providing the data are classified into four groups which are located at the Han river upstream, downstream, the Geum river upstream, and the Nakdong river midstream area. A total of 52 cases were analyzed for seven stations in each group. The optimal exponent value of distance was calculated in a case including one base station and four surrounding stations in a group. We applied the golden section search method to calculating this optimum values using rainfall data for 10 years (2004~2013) and verified the optimum values for the last three years (2014~2016). We compared and analyzed two results of the conventional inverse distance method and the inverse distance method in this study. The optimal values of distance exponent obtained in this study were 3.280, 1.839, 2.181, and 2.005 respectively, in the four groups, and totally mean value was 2.326. It is shown the proposed inverse distance method applying the optimal exponent is superior to the conventional inverse distance method.

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.

Progress Report of the Hubble Constant Determination based on the TRGB Method

  • Jang, In Sung;Lee, Myung Gyoon
    • The Bulletin of The Korean Astronomical Society
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    • v.40 no.1
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    • pp.46.2-46.2
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    • 2015
  • Modern methods in determining the value of the Hubble constant are divided into two main ways: the classical distance ladder method and the inverse distance ladder method. The classical distance ladder method is based on Cepheid calibrated Type Ia supernovae (SNe Ia), which are known as powerful distance indicator. The inverse distance ladder method uses cosmic microwave background radiation, which emitted from the high-z universe, and the cosmological model. Recent estimations of the Hubble constant based on these two methods show a $2{\sim}3{\sigma}$ difference, which called the "Hubble tension". It is currently an issue in the modern cosmology. We have been working on the luminosity calibration of SNe Ia based on the Tip of the Red Giant Branch (TRGB), which is a precise population I distance indicator. We present the TRGB distance estimates of 5 SNe Ia host galaxies with the archival Hubble Space Telescope image data. We derive the mean absolute maximum magnitude of 5 SNe Ia and the value of the Hubble constant. Cosmological implications of our estimate will be discussed.

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Modeling the Natural Occurrence of Selected Dipterocarp Genera in Sarawak, Borneo

  • Teo, Stephen;Phua, Mui-How
    • Journal of Forest and Environmental Science
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    • v.28 no.3
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    • pp.170-178
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    • 2012
  • Dipterocarps or Dipterocarpaceae is a commercially important timber producing and dominant keystone tree family in the rain forests of Borneo. Borneo's landscape is changing at an unprecedented rate in recent years which affects this important biodiversity. This paper attempts to model the natural occurrence (distribution including those areas with natural forests before being converted to other land uses as opposed to current distribution) of dipterocarp species in Sarawak which is important for forest biodiversity conservation and management. Local modeling method of Inverse Distance Weighting was compared with commonly used statistical method (Binary Logistic Regression) to build the best natural distribution models for three genera (12 species) of dipterocarps. Database of species occurrence data and pseudoabsence data were constructed and divided into two halves for model building and validation. For logistic regression modeling, climatic, topographical and edaphic parameters were used. Proxy variables were used to represent the parameters which were highly (p>0.75) correlated to avoid over-fitting. The results show that Inverse Distance Weighting produced the best and consistent prediction with an average accuracy of over 80%. This study demonstrates that local interpolation method can be used for the modeling of natural distribution of dipterocarp species. The Inverse Distance Weighted was proven a better method and the possible reasons are discussed.

New Calibration Methods with Asymmetric Data

  • Kim, Sung-Su
    • The Korean Journal of Applied Statistics
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    • v.23 no.4
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    • pp.759-765
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    • 2010
  • In this paper, two new inverse regression methods are introduced. One is a distance based method, and the other is a likelihood based method. While a model is fitted by minimizing the sum of squared prediction errors of y's and x's in the classical and inverse methods, respectively. In the new distance based method, we simultaneously minimize the sum of both squared prediction errors. In the likelihood based method, we propose an inverse regression with Arnold-Beaver Skew Normal(ABSN) error distribution. Using the cross validation method with an asymmetric real data set, two new and two existing methods are studied based on the relative prediction bias(RBP) criteria.

Development of a Virtual Reference Station-based Correction Generation Technique Using Enhanced Inverse Distance Weighting

  • Tae, Hyunu;Kim, Hye-In;Park, Kwan-Dong
    • Journal of Positioning, Navigation, and Timing
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    • v.4 no.2
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    • pp.79-85
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    • 2015
  • Existing Differential GPS (DGPS) pseudorange correction (PRC) generation techniques based on a virtual reference station cannot effectively assign a weighting factor if the baseline distance between a user and a reference station is not long enough. In this study, a virtual reference station DGPS PRC generation technique was developed based on an enhanced inverse distance weighting method using an exponential function that can maximize a small baseline distance difference due to the dense arrangement of DGPS reference stations in South Korea, and its positioning performance was validated. For the performance verification, the performance of the model developed in this study (EIDW) was compared with those of typical inverse distance weighting (IDW), first- and second-order multiple linear regression analyses (Planar 1 and 2), the model of Abousalem (1996) (Ab_EXP), and the model of Kim (2013) (Kim_EXP). The model developed in the present study had a horizontal accuracy of 53 cm, and the positioning based on the second-order multiple linear regression analysis that showed the highest positioning accuracy among the existing models had a horizontal accuracy of 51 cm, indicating that they have similar levels of performance. Also, when positioning was performed using five reference stations, the horizontal accuracy of the developed model improved by 8 ~ 42% compared to those of the existing models. In particular, the bias was improved by up to 27 cm.

Inverse Offset Method for Adaptive Cutter Path Generation from Point-based Surface

  • Kayal, Prasenjit
    • International Journal of CAD/CAM
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    • v.7 no.1
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    • pp.21-30
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    • 2007
  • The inverse offset method (IOM) is widely used for generating cutter paths from the point-based surface where the surface is characterised by a set of surface points rather than parametric polynomial surface equations. In the IOM, cutter path planning is carried out by specifying the grid sizes, called the step-forward and step-interval distances respectively in the forward and transverse cutting directions. The step-forward distance causes the chordal deviation and the step-forward distance produces the cusp. The chordal deviation and cusp are also functions of local surface slopes and curvatures. As the slopes and curvatures vary over the surface, different step-forward and step-interval distances are appropriate in different areas for obtaining the machined surface accurately and efficiently. In this paper, the chordal deviation and cusp height are calculated in consideration with the surface slopes and curvatures, and their combined effect is used to estimate the machined surface error. An adaptive grid generation algorithm is proposed, which enables the IOM to generate cutter paths adaptively using different step-forward and step-interval distances in different regions rather than constant step-forward and step-interval distances for entire surface.

Estimation of Optimum Pile length Using Various Prediction (다양한 예측기법을 이용한 현장타설말뚝의 최적길이 산정)

  • Choi, Young-Seok;Iim, Hyung-Joon;Song, Myung-Jun;Jang, Hak-Sung
    • Proceedings of the Korean Geotechical Society Conference
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    • 2008.10a
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    • pp.700-707
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    • 2008
  • As plan connecting island to island or island to land is needed, a lot of long-span bridge is being designed lately in Southern part of Korea. With development of pile equipment, overhanging large-scaled concrete pile are adopted to foundation type of main tower or pylon. About the number of 15~30 group piles per tower foundation is designed to resist long-spaning super-structure load, but by restricted condition of site investigation cost, a few boring-hole tests are performed to identify sub-ground layers. Up to now, direct-curved method connecting two or three known boring logs and representative interval method are usually used to evaluate unknown depth and rock properties at locations where piles are constructed. Because this approach is not logical and so rough, much difference occurs between designed length of piles and real length of it. In this paper, using a lot of various prediction method(reciprocal distance method, inverse square distance method and kriging method etc.), we suggest optimum length of group piles.

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Application of Kriging and Inverse Distance Weighting Method for the Estimation of Geo-Layer of Songdo Area in Incheon (인천 송도지역 지층분포 추정을 위한 크리깅과 역거리가중치법의 적용)

  • Kim, Dong-Hee;Ryu, Dong-Woo;Choi, Young-Min;Lee, Woo-Jin
    • Journal of the Korean Geotechnical Society
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    • v.26 no.1
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    • pp.5-19
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    • 2010
  • Geo-layer information is important to determine pile length and estimate residual settlement in the construction site. An overall spatial distribution of geo-layers in the entire construction site can be predicted using drill-log information. In this study, the geo-layer distribution at Song-do area was estimated by kriging and inverse distance weighting methods, and a cross validation was adopted to verify the reliability of estimation results. The analysis results indicate that the best fitted theoretical variogram model to the experimental variogram does not always provide the most reliable estimation in the kriging method. The proper $\alpha$ value of inverse distance weighting method must be determined by types of geo-layer, because the $\alpha$ value is affected by types of geo-layer. Results of the kriging method show more reliable results than those of inverse distance weighting method, and the structure of geo-layer distribution could be evaluated by variogram in the kriging method.

Implementation of Spatial Downscaling Method Based on Gradient and Inverse Distance Squared (GIDS) for High-Resolution Numerical Weather Prediction Data (고해상도 수치예측자료 생산을 위한 경도-역거리 제곱법(GIDS) 기반의 공간 규모 상세화 기법 활용)

  • Yang, Ah-Ryeon;Oh, Su-Bin;Kim, Joowan;Lee, Seung-Woo;Kim, Chun-Ji;Park, Soohyun
    • Atmosphere
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    • v.31 no.2
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    • pp.185-198
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    • 2021
  • In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.