Geohazard Risk Assessment Method Based on Logistic Regression Model

Abstract

Logistic regression model refers a regress analysis contains two types of variants. In geohazard analysis, each geological factor can be defined as independent variable, whether a geohazard happened or not can be defined as a dependent variable. 1 represents an occurrence of a hazard while 0 represents a hazard doesn’t break out. Because those factors aren’t continual variable, lineal regress is inadequate to deduce the relationship of such kind of independent and dependent variable. Therefore using logistic regress method is a feasible way to solve such technique problem.

Landslide hazard zonation using logistic regression technique: the case of Shafe and Baso catchments, Gamo highland, Ethiopia

“…In simple expression when the significance (P) value increases the significance of variation in the observed and expected value becomes less. Most of the statistical analyses afford further statistical validations that may be used to measure the usefulness of the model and that is similar to the coefficient of determination (true R 2 ) in linear regression (Biweck et al 2003;Cheng et al 2012;Nattino et al 2020). Nagelkerke R 2 is used for logistic regression.…”

“…Landslide inventory data for landslide hazard analysis must contain spatial and temporal components or based on rainfall events. The variant of landslide hazard is the presence of the hazard designated as (1) and non-happing of the hazard indicated (0) (Cheng et al 2012). If the dependent variable is binary and the independent factors are containing continuous and discrete variables, the logistic regression method is a widely used statistical approach either for landslide susceptibility or hazard mapping.…”

Research on the Construction of Personal Credit Score Model Based on WOE Analysis and Logistics Model

“…In this paper, the collected data will be sorted and analyzed, and the variables will be screened after determining the variables and their correlations. Then, the logistic regression model [5][6][7] can be transformed into a standard scorecard format by using WOE transformation, and then the model can be tested and the scoring standard can significantly increase the total value of the loan platform loan by improving the accuracy of default prediction. ISSN 2616-5902 Vol.…”