• Title/Summary/Keyword: Gross error testing

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A Study on the Gross Error Elimination of Image Coordinates (상좌표에 포함된 과대오차의 제거방법에 관한 연구)

  • 박홍기;유복모
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.4 no.2
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    • pp.88-93
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    • 1986
  • A gross error of the observation, in least squares abjustment from the linear model, have an effect on the residuals which are correlated. Therefore the testing procedure by Baarda, which is based on the standardized residual, is modified and varied. In is paper, presented methods which have been suggested for multiple gross error elimination are analized, and applied to the gross error elimination of image coordinates.

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A Study on the Model of Artificial Neural Network for Construction Cost Estimation of Educational Facilities at Conceptual Stage (교육시설의 개념단계 공사비예측을 위한 인공신경망모델 개발에 관한 연구)

  • Son, Jae-Ho;Kim, Chung-Yung
    • Korean Journal of Construction Engineering and Management
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    • v.7 no.4 s.32
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    • pp.91-99
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    • 2006
  • The purpose of this study is propose an Artificial Neural Network(ANN) model for the construction estimate of the public educational facility at conceptual stage. The current method for the preliminary cost estimate of the public educational facility uses a single-parameter which is based on basic criteria such as a gross floor area. However, its accuracy is low due to the nature of the method. When the difference between the conceptual estimate and detailed estimate is huge, the project has to be modified to meet the established budget. Thus, the ANN model is developed by using multi-parameters in order to estimate the project budget cost more accurately. The result of the research shows 6.82% of the testing error rates when the developed model was tested. The error rates and the error range of the developed model are smaller than those of the general preliminary estimating model at conceptual stage. Since the proposed ANN model was trained using the detailed estimate information of the past 5 years' school construction data, it is expected to forecast the school project cost accurately.

Adjustment of 1st order Level Network of Korea in 2006 (2006년 우리나라 1등 수준망 조정)

  • Lee, Chang-Kyung;Suh, Young-Cheol;Jeon, Bu-Nam;Song, Chang-Hyun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.26 no.1
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    • pp.17-26
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    • 2008
  • The 1st order level network of Korea was adjusted simultaneously in 1987. After that, the 1 st order level network of Korea was adjusted simultaneously by National Geographic Information Institute in 2006. The levelling data were acquired by digital level with invar staff from 2001 through 2006. The 1st order level network consists of 36 level lines. Among them, 34 level lines comprise 11 level loops. Among 36 level lines, 4 level lines have fore & back error larger than the regulations for the 1st order levelling of NGII, Korea. Also, the closing error of 3 loops of level network exceed the regulation for the 1st order levelling of NGII. The standard error of fore and back leveling between bench marks(${\eta}_1$) are distributed between 0.2 $mm/{\surd}km$ and 1.7 $mm/{\surd}km$. The standard error of loop closing(${\eta}_2$) is 2.0 $mm/{\surd}km$. This result means that the 1st order level network of Korea qualifies for the high precision leveling defined by International Geodetic Association in 1948. As the result of the 1st order level network adjustment, the reference standard error($\hat{{\sigma}_0}$) of the level network was 1.8 $mm/{\surd}km$, which is twice as good as that of the 1st adjustment of level networks in 1987.

Relationship among FDI, Economic Growth, and Employment (외국인직접투자와 경제성장 및 고용간 관계)

  • Kang, Gi-Choon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.12
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    • pp.574-580
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    • 2019
  • In this paper, the economic performance of the Jeju Free International City and the Free Economic Zone is investigated using statistical testing and the difference in differences (DID) model with data on foreign direct investment (FDI), gross regional domestic product (GRDP), and employment-to-population ratio (EPR). The relationships among FDI, GRDP, and EPR are also investigated using the panel vector error-correction model on the regional data. The compound average growth rate of actual investment, and the ratio of FDI received to FDI declared in the capital region were higher than in the non-capital region. For the growth and relative volume of FDI received, seven regions out of 16 were found to be low in growth and small in relative volume. The results of statistical testing showed statistically significant differences in some variables, except for two regions, but DID estimates that determine the pure policy effect of zone designation showed statistical insignificance. On the other hand, the explanatory power among the three variables was found to be quite limited, but it was greater in the cities, provinces, and non-capital region. In summary, it is necessary to establish the FDI inducement mechanism so the inflow of FDI can increase GRDP and EPR.