• Title/Summary/Keyword: logistic analysis

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Analysis of Landslide Hazard Area using Logistic Regression Analysis and AHP (Analytical Hierarchy Process) Approach (로지스틱 회귀분석 및 AHP 기법을 이용한 산사태 위험지역 분석)

  • Lee, Yong-jun;Park, Geun-Ae;Kim, Seong-Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.5D
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    • pp.861-867
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    • 2006
  • The objective of this study is to analyze the landslide hazard areas by combining LRA (Lgistic Regression Analysis) and AHP (Analytic Hierarchy Program) methods with Remote Sensing and GIS data in Anseong-si. In order to classify landslide hazard areas of seven levels, six topographic factors (slope, aspect, elevation, soil drain, soil depth, and land use) were used as input factors of LRA and AHP methods. As results, high-risk areas for landslide (1 and 2 levels) by LRA and AHP of its own were classified as 46.1% and 48.7%, respectively. A new method by applying weighting factors to the results of LRA and AHP was suggested. High-risk areas for landslide (1 and 2 levels) form the new method was classified as 58.9%.

Study on Accident Prediction Models in Urban Railway Casualty Accidents Using Logistic Regression Analysis Model (로지스틱회귀분석 모델을 활용한 도시철도 사상사고 사고예측모형 개발에 대한 연구)

  • Jin, Soo-Bong;Lee, Jong-Woo
    • Journal of the Korean Society for Railway
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    • v.20 no.4
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    • pp.482-490
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    • 2017
  • This study is a railway accident investigation statistic study with the purpose of prediction and classification of accident severity. Linear regression models have some difficulties in classifying accident severity, but a logistic regression model can be used to overcome the weaknesses of linear regression models. The logistic regression model is applied to escalator (E/S) accidents in all stations on 5~8 lines of the Seoul Metro, using data mining techniques such as logistic regression analysis. The forecasting variables of E/S accidents in urban railway stations are considered, such as passenger age, drinking, overall situation, behavior, and handrail grip. In the overall accuracy analysis, the logistic regression accuracy is explained 76.7%. According to the results of this analysis, it has been confirmed that the accuracy and the level of significance of the logistic regression analysis make it a useful data mining technique to establish an accident severity prediction model for urban railway casualty accidents.

Application of Crossover Analysis-logistic Regression in the Assessment of Gene- environmental Interactions for Colorectal Cancer

  • Wu, Ya-Zhou;Yang, Huan;Zhang, Ling;Zhang, Yan-Qi;Liu, Ling;Yi, Dong;Cao, Jia
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.5
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    • pp.2031-2037
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    • 2012
  • Background: Analysis of gene-gene and gene-environment interactions for complex multifactorial human disease faces challenges regarding statistical methodology. One major difficulty is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes or environmental exposures. Based on our previous case-control study in Chongqing of China, we have found increased risk of colorectal cancer exists in individuals carrying a novel homozygous TT at locus rs1329149 and known homozygous AA at locus rs671. Methods: In this study, we proposed statistical method-crossover analysis in combination with logistic regression model, to further analyze our data and focus on assessing gene-environmental interactions for colorectal cancer. Results: The results of the crossover analysis showed that there are possible multiplicative interactions between loci rs671 and rs1329149 with alcohol consumption. Multifactorial logistic regression analysis also validated that loci rs671 and rs1329149 both exhibited a multiplicative interaction with alcohol consumption. Moreover, we also found additive interactions between any pair of two factors (among the four risk factors: gene loci rs671, rs1329149, age and alcohol consumption) through the crossover analysis, which was not evident on logistic regression. Conclusions: In conclusion, the method based on crossover analysis-logistic regression is successful in assessing additive and multiplicative gene-environment interactions, and in revealing synergistic effects of gene loci rs671 and rs1329149 with alcohol consumption in the pathogenesis and development of colorectal cancer.

Uncertainty Analysis of the Risk of Hydraulic Structures Using Generalized Logistic Distribution (Generalized Logistic 분포형을 이용한 수공구조물의 위험도에 대한 불확실성 해석)

  • Shin, Hong-Joon;Heo, Jun-Haeng
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.758-763
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    • 2006
  • Statistical concepts and methods are routinely utilized in a number of design and management problems in engineering hydrology. This is because most of hydrological processes have some degree of randomness and uncertainty. Thus, the concepts of risk and uncertainty are commonly utilized for designing and evaluating hydraulic structures such as spillways and dikes. Therefore, in this study, uncertainty analysis considering the variance of design floods is performed to evaluate the uncertainty of the hydrologic risk of flood related hydraulic structures using frequency analysis.

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Rationalization Of Logistic System Through Practical Survey And Analysis. (실증적 연구에 의한 물류시스템 합리화 방안)

  • 서경범
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.17 no.32
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    • pp.163-175
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    • 1994
  • This paper is to establish rational logistic system practical study between korea and Japan. In this paper the five logistic function of korea business are classified and investigated and analyzed. And two, i.e., strategic and tactic, aspects of logistic system between two nations are compared with each other through practical study Finally this Paper Proposes a integrated logistic system exploiting the strength of both nations.

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Uncertainty Assessment of Regional Frequency Analysis for Generalized Logistic Distribution (Generalized Logistic 분포형을 이용한 지역빈도해석의 불확실성 추정)

  • Shin, Hongjoon;Nam, Woosung;Jung, Younghun;Heo, Jun-Haeng
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6B
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    • pp.723-729
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    • 2008
  • Confidence intervals of growth curves are calculated to assess the uncertainty of index flood method as a regional frequency analysis. The asymptotic variance of quantile estimator for the generalized logistic distribution is introduced to evaluate confidence intervals. In addition, the variances of at-site frequency estimator and regional frequency estimator are used to evaluate an efficiency index. The efficiency indexes for 14 homogeneous regions based on 378 stations show that index flood method estimators are more efficient than at-site frequency estimators. It is shown that the number of sites in a region needs to be limited for regional gain.

Logistic Supportability Improvement Program for the Future Main Battle Tank (고장진단체계 구축을 통한 미래전차의 군수지원성 향상 방안 연구)

  • Jung, ChangMo;Lee, MyungChun
    • Journal of the Korean Society of Systems Engineering
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    • v.1 no.2
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    • pp.34-42
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    • 2005
  • Logistic Support Analysis(LSA) and Logistic Supportability Review must be carried out as soon as possible in development stage in order to minimize operation/maintenance cost that head the list of weapon cost and improve logistic supportability of the weapon system. And the result must be used for hardware designs to set up to be able to input to the system design and logistic support elements. Therefore Logistic Support Elements must be planed/developed/supplied with the main combat system concurrently and performance and logistic supportability of the comabat system had better be improved mutually. This report describes maintenance concept changes of weapon systems, fault diagnosis function and test equipment state on the domestic MBT(main battle tank). And then it presents application and intensification of itself fault diagnosis system for a domestic future MBT considering connection with IETM(Interactive Electronic Technical Manual) and TE(Test Equipment).

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Economic Effects of Establishing a Logistic Free Zone in the Port of Busan (물류중심형 자유지대의 경제적 파급효과에 관한 연구 - 부산항을 중심으로 -)

  • Sohn, Ae-Hwi
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2000.11a
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    • pp.33.2-42
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    • 2000
  • This study probes the necessity of establishing a logistic free zone in Port of Busan. It considers the economic effects of establishing the logistic free zone of Busan Port, and suggests policy prescriptions for introducing the free zone system and improving the logistics functions of Busan Port. Using input-output table data, the regression analysis was able to provide a quantitative prediction on effects of making the Busan Port a tariff-free zone. Influence for the regional economy due to the enforcement of the free zone system this research found that a strong positive effects should be expected on the Busan regional economy once the logistic free zone would be set up at the Port of Busan. The positive economic effects on Busan regional industries might be further strengthened if the value-added logistics function of Busan Port could be supplemented by linking to the hinterland of Busan Port.

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A Logistic Regression Analysis of Two-Way Binary Attribute Data (이원 이항 계수치 자료의 로지스틱 회귀 분석)

  • Ahn, Hae-Il
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.35 no.3
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    • pp.118-128
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    • 2012
  • An attempt is given to the problem of analyzing the two-way binary attribute data using the logistic regression model in order to find a sound statistical methodology. It is demonstrated that the analysis of variance (ANOVA) may not be good enough, especially for the case that the proportion is very low or high. The logistic transformation of proportion data could be a help, but not sound in the statistical sense. Meanwhile, the adoption of generalized least squares (GLS) method entails much to estimate the variance-covariance matrix. On the other hand, the logistic regression methodology provides sound statistical means in estimating related confidence intervals and testing the significance of model parameters. Based on simulated data, the efficiencies of estimates are ensured with a view to demonstrate the usefulness of the methodology.

Landslide Susceptibility Analysis and its Verification using Likelihood Ratio, Logistic Regression and Artificial Neural Network Methods: Case study of Yongin, Korea

  • Lee, S.;Ryu, J. H.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.132-134
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    • 2003
  • The likelihood ratio, logistic regression and artificial neural networks methods are applied and verified for analysis of landslide susceptibility in Yongin, Korea using GIS. From a spatial database containing such data as landslide location, topography, soil, forest, geology and land use, the 14 landsliderelated factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression and artificial neural network methods. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the methods. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The v erification results showed satisfactory agreement between the susceptibility map and the exis ting data on landslide locations.

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