• Title/Summary/Keyword: 수량화

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Evaluation of Road Plan using Information Measure Technique and GIS (정보계측기법과 지리정보시스템을 이용한 도로계획의 평가)

  • Na, Joon-Yeop
    • Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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    • 2007.10a
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    • pp.239-246
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    • 2007
  • 공공시설 중 도로계획의 경우 건설과정 및 건설 후의 소음 및 오염 등의 환경 사회적 비용 및 주행성 안전성 등 요소의 평가 등을 수량화가 어려운 대표적 비용으로 들 수 있는데 본 연구에서는 이러한 수량화가 어려운 비용 효과들을 포함하여 고려한 도로노선계획결과를 정보계측기법과 지리정보시스템을 이용하여 '정보량'이라는 통일된 단위로 표현하고, 기존 시설물과의 관계로부터의 '정보편익' 개념으로 평가하였다. 정보계측기법은 인간은 언어를 통하여 모든 사물을 정보로 표현하므로 '정보'라는 통일 된 단위를 사용하여 모호한 가치를 평가해 보고자 하는 방법이며, 따라서 공공시설의 계획과정에서 최적해를 찾기 위한 비용, 편익 및 환경 사회적 요소 등의 정량화되기 어려운 가치를 평가하는데도 사용될 수 있을 것이다. 정보계측기법과 지리정보시스템을 이용하여 도로건설시 발생하는 비용과 직접효과를 고려하기 위하여 시설정보계측모형을 개발하였으며, 도로 주변 시설간의 편익을 고려하기 위하여 시설정보편익모형을 구성하였다. 개발된 모형을 실제 도로계획 사례에 적용한 결과 비용과 직접효과만을 고려한 시설정보계측모형에서는 기존의 도로설계와 유사한 결과가 도출되었으며, 시설정보편익모형에서는 기존의 도로계획 평가에서 고려할 수 없었던 요소들에 대한 고려가 가능하였다.

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A Study on Geological Factors Affecting Behavior of Sedimentary Rock Tunnel Using Quantification Method Type I (수량화방법 I을 이용한 퇴적암 터널의 지질 인자별 변위 영향도 분석)

  • Yim, Sung-Bin;Seo, Yong-Seok;Kim, Chang-Yong;Kim, Kwang-Yoem
    • The Journal of Engineering Geology
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    • v.17 no.2 s.52
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    • pp.263-270
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    • 2007
  • Tunnel behavior measured by monitoring during construction is a main item for safety evaluation and it depends widely upon local geological characteristics. To assess in this study how much the geological factors influence on tunnel behavior for each RMR factor, a quantification analysis was carried out using tunnel face maps and measurements as explanatory variables and dependent variables, respectively. The results showed that average significance of the influence of RMR factors - R1, R2, R3, R4 and R5, on tunnel displacements are 17.0%, 20.4%, 20.4%, 11.6% and 30.6%, respectively, and this probably indicates that the groundwater condition played a significant role for the tunnel displacement.

GIS Based Analysis of Landslide Factor Effect in Inje Area Using the Theory of Quantification II (수량화 2종법을 이용한 GIS 기반의 인제지역 산사태 영향인자 분석)

  • Kim, Gi-Hong;Lee, Hwan-Gil
    • Spatial Information Research
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    • v.20 no.3
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    • pp.57-66
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    • 2012
  • Gangwon-do has been suffering extensive landslide dam age, because its geography consists mainly of mountains. Analyzing the related factors is crucial for landslide prediction. We digitized the landslide and non-landslide spots on an aerial photo obtained right after a disaster in Inje, Gangwon-do. Three landslide factors-topographic, forest type, and soil factors-w ere statistically analyzed through GIS overlap analysis between topographic map, forest type map, and soil map. The analysis showed that landslides occurred mainly between the inclination of $20^{\circ}$ and $35^{\circ}$, and needleleaf tree area is more vulnerable to a landslide. About soil properties, an area with shallow effective soil depth and parent material of acidic rock has a greater chance of landslide.

A Study on Discriminant.Classification Model of Impact Factors about Understanding of Traffic Accident Causes and Acknowledgement to Decrease Traffic Accidents (교통사고 발생원인 인식과 감소대책 인지 영향요인 판별.분류에 관한 연구)

  • 고상선;배기목;이원규;정헌영
    • Journal of Korean Society of Transportation
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    • v.20 no.7
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    • pp.143-153
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    • 2002
  • 본 연구는 교통사고의 발생원인에 대한 인식유형과 감소대책에 대한 인지 유형별 영향요인의 정도를 분석하기 위하여 수량화이론 II류와 CHAID 분석법을 이용하여 분류모델과 판별모델을 구축하였다. 수량화이론 II류에 의한 교통사고 발생원인에 대한 인식 유형별 영향요인 판별모델은 전체 적중률이 78.4%로 매우 높게 나타났다. 편상관계수는 설명변수의 항목 중 학력, 성별, 운전경력 년 수, 소유 차종의 순으로 영향을 미치고 외적 변수인 교통사고 발생원인에 대한 유형에서는 기여 정도가 교통단속 부재 > 교통체계 미비 > 승용차 과다 사용 >잘못된 의식 때문의 순으로 나타났다. 교통사고 감소 대책에 대한 인지유형별 영향요인 판별모델은 전체 적중률이 59.9%로 높게 나타났으며, 편상관 계수는 학력, 성별, 운전경력 연수, 연령의 순으로 영향을 미치고 있고, 외적 변수인 교통사고 감소 대책에 대한 유형에서는 기여 정도가 교통단속 강화 > 대중교통수단 이용 유도 > 교통체계 개선 > 의식 개혁의 순으로 나타났다. 또한 CHAID 분석법에 의한 교통사고 발생원인에 대한 인식 유형별 영향요인 분류모델에 있어서는 예측변수로 학력, 연령, 성별, 통행수단의 네 가지 변수가, 교통사고의 감소 대책에 대한인지 유형별 영향요인 분류모델에 있어서는 학력, 운전경력 연수, 성별 그리고 통행수단의 네 가지 변수가 카이제곱 통계량 이 5%의 유의수준에서 유의한 것으로 판단되었다. 교통사고 발생원인 인식과 감소 대책의 인지 유형에 대한 빈도분석과 교차분석은 의식과 관련한 유형이 가장 높게 나타났으나 판별.분류모델에서는 교통단속과 관련한 유형이 기여 정도가 높고 의식 관련 유형이 상대적으로 낮게 나타나는 등 반대양상을 보이고 있어 심리적으로 내재되어 있고 표면에 잘 드러나지 않았던 의식 수준의 낮음이 분류모델을 통해서 명확하게 드러났다.

Suggestion of an Evaluation Chart for Landslide Susceptibility using a Quantification Analysis based on Canonical Correlation (정준상관 기반의 수량화분석에 의한 산사태 취약성 평가기법 제안)

  • Chae, Byung-Gon;Seo, Yong-Seok
    • Economic and Environmental Geology
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    • v.43 no.4
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    • pp.381-391
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    • 2010
  • Probabilistic prediction methods of landslides which have been developed in recent can be reliable with premise of detailed survey and analysis based on deep and special knowledge. However, landslide susceptibility should also be analyzed with some reliable and simple methods by various people such as government officials and engineering geologists who do not have deep statistical knowledge at the moment of hazards. Therefore, this study suggests an evaluation chart of landslide susceptibility with high reliability drawn by accurate statistical approaches, which the chart can be understood easily and utilized for both specialists and non-specialists. The evaluation chart was developed by a quantification method based on canonical correlation analysis using the data of geology, topography, and soil property of landslides in Korea. This study analyzed field data and laboratory test results and determined influential factors and rating values of each factor. The quantification analysis result shows that slope angle has the highest significance among the factors and elevation, permeability coefficient, porosity, lithology, and dry density are important in descending order. Based on the score assigned to each evaluation factor, an evaluation chart of landslide susceptibility was developed with rating values in each class of a factor. It is possible for an analyst to identify susceptibility degree of a landslide by checking each property of an evaluation factor and calculating sum of the rating values. This result can also be used to draw landslide susceptibility maps based on GIS techniques.

Derivation of Suitable-Site Environmental Factors in Robinia pseudoacacia Stands Using Type I Quantification Theory (수량화이론 I방법에 의한 아까시나무 임분의 적지 환경인자 도출)

  • Kim, Sora;Song, Jungeun;Park, Chunhee;Min, Suhui;Hong, Sunghee;Lim, Jongsoo;Son, Yeongmo
    • Journal of Korean Society of Forest Science
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    • v.111 no.3
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    • pp.428-434
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    • 2022
  • This study was conducted to derive the site index of forest productivity of Robinia pseudoacacia (honey plant) to characterize suitable planting sites and to investigate the effect of the site environmental factors on the site index using the quantification theory I method. The data used in the analysis were growth factors (stand age, dominant height, etc.) of the 6th national forest resources survey and various site environmental factors of a forest soil map (1:5,000). The average site index value of the R. pseudoacacia stand in Korea was 14 (range, 8 to 18). The environmental factors affecting the site index were parent rock, climatic zone, soil texture, local topography, and altitude. The accuracy of the estimation model using quantification theory I was only 33%. However, the correlation between the site index and the site environmental factors was statistically significant at the 1% level. Results of quantification analysis between site index and site environmental factors revealed that metamorphic and igneous rocks received high grades as parent rocks, climate zones received higher grades than central temperate zone, clay loam and silt loam received high grades in soil texture, and hillside received a high grade in local topography. Analysis of the partial correlation between site topographical factors and forest productivity (site index) found that soil class and altitude were partially correlated to x by 0.4129 and 0.4023, respectively, indicating that these factors are the most influential variables.

Visualizing (X,Y) Data by Partial Least Squares Method (PLS 기법에 의한 (X,Y) 자료의 시각화)

  • Huh, Myung-Hoe;Lee, Yong-Goo;Yi, Seong-Keun
    • The Korean Journal of Applied Statistics
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    • v.20 no.2
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    • pp.345-355
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    • 2007
  • PLS methods are suited for regressing q-variate Y variables on p-variate X variables even in the presence of multicollinearity problem among X variables. Consequently, they are useful for analyzing datasets with smaller number of observations compared to the number of variables, such as NIR(near-infrared) spectroscopy data in chemometrics. In this study, we propose two visualizing methods of p-variate X variables and q-variate Y variable that can be used in connection with PLS analysis.

The Evaluation of Failure Factors on Cutting Slopes of Forest Road by Quantification Theory(II) (수량화 II 류에 의한 임도절토사면의 붕괴요인 평가)

  • Cha, Du-Song;Ji, Byoung-Yun
    • Journal of Forest and Environmental Science
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    • v.18 no.1
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    • pp.7-14
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    • 2001
  • On the basis of data obtained from forest road collapsed due to a heavy rainfall, this study carried out to evaluate the cutting slope failure factors of forest road by using Quantification theory(II). The results were summarized as follows. The factors on cutting slope failure was ranked in the order of cutting slope length, soil type, aspect, cutting slope gradients and slope gradients. And the slope failure was mainly occurred under such conditions as cutting slope length longer than 8m, soil type with soil, aspect of N, cutting slope gradients steeper than 600 and slope gradients greater than $35{\sim}40^{\circ}$.

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Quantification Method of Tunnel Face Classification Using Canonical Correlation Analysis (정준상관분석을 이용한 막장등급평가 수량화기법 연구)

  • Seo Yong-Seok;Kim Chang-Yong;Kim Kwang-Yeom;Lee Hyun-Woo
    • The Journal of Engineering Geology
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    • v.15 no.4 s.42
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    • pp.463-473
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    • 2005
  • Because of using the same rating ranges for every rock types the RMR or the Q-system could not usually consider local geological characteristics They also could not present sufficiently the engineering anisotropy of rocks. The canonical correlation analysis was carried out with 3 kinds of face mapping data obtained from granite, sedimentary rock and phyllite in order to clarify a discrepancy between rock types. According to analysis results, as a type of rocks changes, RM factors have different influences on the total rating of RMR.