• 제목/요약/키워드: accuracy index

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산지돌발홍수 예측을 위한 TOPLATS 지표해석모델 적용성 평가 (The Evaluation of TOPLATS Land Surface Model Application for Forecasting Flash Flood in mountainous areas)

  • 이병주;최수민;윤성심;최영진
    • 한국수자원학회논문집
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    • 제49권1호
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    • pp.19-28
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    • 2016
  • 본 연구의 목적은 TOPLATS 지표해석모형으로부터 생산된 격자 수문기상성분과 통계적 돌발홍수지수모형을 이용하여 격자 돌발홍수지수를 생산하고 그 적용성을 평가하는데 있다. 대상유역은 2009~2012년동안 38건의 돌발홍수 구조요청 사례가 발생한 수도권 지역을 선정하였다. 지표해석모형의 시공간 해상도는 1 h, 1 km 이며 동일한 해상도의 모의를 위해 필요한 격자 기상자료는 기상청 AWS (automatic weather stations)의 시단위 자료를 역거리법을 이용하여 구축하였다. 돌발홍수 피해사례 38건에 대해 대응되는 모의격자의 수문성분을 분석하였으며 27건(71%)에서 구조요청시점에 대해 강우량, 지표유출량, 토양수분량, 지하수면깊이가 적절하게 모의되는 것을 확인하였다. 강우조건에 따른 격자 돌발홍수지수의 정확도는 구조요청시점 기준 선행시간 4~6시간까지 71~87%, 구조요청시점으로 한정된 0시간에서 42~52%로 나타났다. 이상의 결과로부터 지표해석모델을 이용한 격자 수문성분과 통계적 돌발홍수지수모형으로부터 산정된 격자 돌발홍수지수는 산지 돌발홍수를 예측하는데 활용될 수 있을 것으로 판단된다.

Landsat-8 위성영상 기반 수분지수 및 기계학습을 활용한 대구광역시의 지표수 탐지 (Detection of Surface Water Bodies in Daegu Using Various Water Indices and Machine Learning Technique Based on the Landsat-8 Satellite Image)

  • 정윤재;김경섭;박인선;정연인
    • 한국지리정보학회지
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    • 제24권1호
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    • pp.1-11
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    • 2021
  • 위성영상을 활용한 하천, 습지, 호수 등 지표수 객체의 탐지는 해당 지역의 수자원 관리 및 조사 업무에 효율적으로 활용될 수 있다. 본 연구에서는 원격탐사 분야에서 물을 탐지하기 위해 제공하는 수분지수(Water Index)와 영상으로부터 객체를 인식하는 데 폭넓게 활용되는 기계학습(Machine learning) 기법을 대구광역시를 촬영한 Landsat-8 위성영상에 개별적으로 적용하여 하천, 호수 등 다양한 지표수 객체를 탐지하고 그 결과를 비교하였다. 우선 Landsat-8 위성영상의 다중분광 밴드로부터 NDWI(Normalized Difference Water Index), MNDWI(Modified Normalized Difference Water Index) 영상을 생성하였고, 임계치를 적용하여 개별 영상으로부터 물과 그 외 지역을 구분할 수 있는 이진 영상(Binary image)을 제작하였다. 그리고 기계학습 기법인 SVM(Support Vector Machine)을 동일 위성영상에 적용하여 토지 피복 영상을 제작하고 이로부터 이진 영상을 제작하였다. 최종적으로 100개의 검사점(Checkpoints)을 사용하여 세 이진 영상으로부터 지표수 탐지를 위한 정확도를 오차 행렬을 활용하여 계산하였다. 그 결과, MNDWI 영상으로부터 제작된 이진 영상의 정확도(84%)가 NDWI 영상으로부터 제작된 이진 영상의 정확도(94%)와 SVM에 의해 제작된 이진 영상의 정확도(96%)에 비해 낮았으며, 모든 이진 영상에서 그림자 등의 원인으로 인해 일부 육지 분류 결과가 지표수 객체로 오분류되었다.

Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index

  • Bae, Sunghwan;Choi, Sungkyoung;Kim, Sung Min;Park, Taesung
    • Genomics & Informatics
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    • 제14권4호
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    • pp.149-159
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    • 2016
  • With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

산사태 발생지 예측을 위한 Topographic Position Index의 적용성 연구 (Study on Application of Topographic Position Index for Prediction of the Landslide Occurrence)

  • 우충식;이창우;정용호
    • 한국환경복원기술학회지
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    • 제11권2호
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    • pp.1-9
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    • 2008
  • The objective of the study is 10 know the relation of landslide occurrence with using TPI (Topographic Position Index) in the Pyungchang County. Total 659 landslide scars were detected from aerial photographs. To analyze TPI, 100m SN (Small-Neighborhood) TPI map, 500m LN (Large-Neighborhood) TPI map, and slope map were generated from the DEM (Digital Elevation Model) data which are made from 1 : 5,000 digital topographic map. 10 classes clustered by regular condition after overlapping each TPI maps and slope map. Through this process, we could make landform classification map. Because it is only to classify landform, 7 classes were finally regrouped by the slope angle information of landslide occurrence detected from aerial photography analysis. The accuracy of reclassified map is about 46%.

압밀시험의 교란정도 추정 (Evaluation of the Degree of Disturbance on Oedometer Test)

  • 전남수;최명진;김팔규
    • 한국지반공학회:학술대회논문집
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    • 한국지반공학회 2000년도 가을 학술발표회 논문집
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    • pp.369-376
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    • 2000
  • Parameters that represent the characteristic of consolidation have been determined by the oedometer tests. They are varied by the process of sampling and transportation, accuracy of apparatus, process of sample trimming and the skill of engineers. Also, it is difficult to grasp what factor exert a influence on the parameters. In this study, Slurry Rowe Cell Tests were peformed to evaluate the disturbance. Using the plot of e - log p which obtained from Rowe Cell test results, we compared the swelling indexes at the stress relief and the last loading stage. With that result, we tried to presume the disturbance of the 330 oedometer tests. The plot of compression-swelling index at the stress relief considerably scattered but at the last step of load shows a correlations between them. And the plot of depth-p$\sub$c/ shows a correlation with the different swelling indexes, but not in the LL-p$\sub$c/. Consequently, it is considered that the disturbance of the consolidation tests can be presumed by the comparison of the difference of swelling index.

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An Evolutionary Approach to Inferring Decision Rules from Stock Price Index Predictions of Experts

  • Kim, Myoung-Jong
    • Management Science and Financial Engineering
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    • 제15권2호
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    • pp.101-118
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    • 2009
  • In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

A New Assessment for the Total Harmonic Contributions at the Point of Common Coupling

  • Han, Jong-Hoon;Lee, Kyebyung;Song, Chong Suk;Jang, Gilsoo;Byeon, Gilsung;Park, Chang-Hyun
    • Journal of Electrical Engineering and Technology
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    • 제9권1호
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    • pp.6-14
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    • 2014
  • A new method to determine the total harmonic contributions of several customers and the utility at the point of common coupling is presented. The proposed method can quantify the individual harmonic impact of each suspicious harmonic source at the point of common coupling. The individual harmonic impact index is then used to assess the total harmonic contribution of each harmonic source. This index can be calculated by the results processed from instantaneous harmonic voltage and current phasor values. The results demonstrate the performance of the proposed method in terms of steady-state accuracy and response to time-varying operating conditions. The proposed index can be used for billing purposes to control harmonic distortion levels in power systems.

Estimation of River Pollution Index Using Landsat Imagery over Tamsui River, Taiwan

  • Wang, Ying Hsuan;Sohn, Hong-Gyoo
    • Ecology and Resilient Infrastructure
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    • 제5권2호
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    • pp.88-93
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    • 2018
  • In-situ water quality sampling is used for accurate water quality assessment. However, in-situ water quality sampling offers limited samples and requires much time and intensive labors. Remote sensing approach has recently applied for water quality assessment. It has shown the advantage of offering a synoptic view but also more efficient and economical. In this study, we utilized Landsat Imagery to estimate the water quality of the Tamsui River basin, considered as one of the most important rivers located in the north of Taiwan. In order to monitor water quality of Tamsui River basin, a linear regression relation between the value of spectral radiance and four water quality parameters are investigated with 38 water sampling stations. Through the regression model, we could estimate river pollution index (RPI) from the predicted value of four water quality parameters. By using RPI, we can examine the pollution level of Tamsui River. The accuracy of RPI conversion of this study ranged from 32.2% to 68.2%.

국가승인통계 품질 등급 부여 및 상대지표 개발 (Research on grading the quality level and developing the comparability index of the national statistics)

  • 심규호
    • 품질경영학회지
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    • 제38권2호
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    • pp.150-160
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    • 2010
  • Statistics Korea has been diagnosis national statistics every year since 2006. They diagnosis over 200 kinds of national statistics. They have 7 quality dimension used for quality diagnosis. That is relevance, accuracy, Timeliness, Comparability, Coherence, Accessibility. Since we are interest in how well they produce national statistics, comparability has become the most important dimension recently. In this reason, Statistics Korea try to rating quality level and development comparability index for national statistics. This paper propose the practical method of grading the quality level and developing the comparability index of the national statistics.

A study on evaluating the spatial distribution of satellite image classification error

  • Kim, Yong-Il;Lee, Byoung-Kil;Chae, Myung-Ki
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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    • pp.213-217
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    • 1998
  • This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

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