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Landslide susceptibility modeling using bivariate statistical-based logistic regression, naïve Bayes, and alternating decision tree models
The main aim of this study is to use weights of evidence (WoE), logistic regression (LR), naïve Bayes (NB), and alternating decision tree (ADTree)...
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Flood hazard map** using M5 tree algorithms and logistic regression: a case study in East Black Sea Region
Flood is a type of disaster that occurs as a result of the overflow of the stream outside its bed. Similarly to many parts of the globe, particularly...
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An Integrated Framework for Data-Driven Mineral Prospectivity Map** Using Bagging-Based Positive-Unlabeled Learning and Bayesian Cost-Sensitive Logistic Regression
Mineral prospectivity map** (MPM) is a spatial quantitative approach to delineation of exploration targets. The input data and the data integration...
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Methodology for Estimating Streamflow by Water Balance and Rating Curve Methods Based on Logistic Regression
Both water balance (WB) and rating curve (RC) are methods for estimating streamflow. The first is mostly used to estimate reservoir outflows, while...
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Integration and comparison of algorithmic weight of evidence and logistic regression in landslide susceptibility map** of the Orumba North erosion-prone region, Nigeria
In recent times, weight of evidence (WoE) and logistic regression (LR) methods in GIS-based landslide susceptibility map** (LSM) have been remarked...
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Spatio-temporal prediction and map** of landslides using MTInSAR-learning logistic regression and weight of evidence modeling in urban environments: a case study for the Büyükçekmece–Küçükçekmece region, İstanbul, Türkiye
The megacity İstanbul (Türkiye) is rapidly urbanizing with a high population growth. Similar to this, the region of İstanbul Metropole between the...
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Landslide Susceptibility Zonation Map** Using Frequency Ratio, Information Value Model, and Logistic Regression Model: A Case Study of Kohima District in Nagaland, India
Landslide is one of the most dangerous natural hazards in hilly terrain areas and cause severe damage to life, property, and socio-economics. Proper...
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Application of logistic regression model for hazard assessment of landslides caused by the 2012 Yiliang Ms 5.7 earthquake in Yunnan Province, China
Accurate assessment of seismic landslides hazard is a prerequisite and foundation for post-disaster relief of earthquakes. An Ms 5.7 earthquake...
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GIS-based evaluation of water-inrush risk from coal floor using logistic regression and certainty factor models
With the gradual increase in coal mining depth in China, the threat of floor water disaster in coal mines is also increasing. The risk assessment of...
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Integrating vegetation indices and geo-environmental factors in GIS-based landslide-susceptibility map**: using logistic regression
This study aimed to assess the potential of in-situ measured soil and vegetation characteristics in landslide susceptibility analyses. First, data...
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Random Forest and Logistic Regression algorithms for prediction of groundwater contamination using ammonia concentration
The present study aims to develop an efficient predictive model for groundwater contamination using Multivariate Logistic Regression (MLR) and Random...
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Effectiveness of Newmark-based sampling strategy for coseismic landslide susceptibility map** using deep learning, support vector machine, and logistic regression
Non-landslide samples play a crucial role in landslide susceptibility map** (LSM), although unsuitable sampling methods may degrade the performance...
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Impacts of anthropogenic and biophysical factors on ecological land using logistic regression and random forest: A case study in Mentougou District, Bei**g, China
Ecological land is an important guarantee to maintain urban ecological security and sustainable development. Although increasing studies have been...
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Comparison of LR, 5-CV SVM, GA SVM, and PSO SVM for landslide susceptibility assessment in Tibetan Plateau area, China
The applicability of statistics-based landslide susceptibility assessment methods is affected by the number of historical landslides. Previous...
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Identifying river bank erosion potential zones through geo-spatial and binary logistic regression modeling approach: a case study of river Ganga in Malda district (India)
This study aims to evaluate the causative factors for high bank erosion probability along the left bank of Ganga river in Malda district using binary...
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Landslide susceptibility map** using maximum entropy (MaxEnt) and geographically weighted logistic regression (GWLR) models in the Río Aguas catchment (Almería, SE Spain)
A landslide susceptibility analysis has been made in the Río Aguas catchment (Almeria, Southeast Spain), using two statistical models, Maximum...
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Optimal flood susceptibility model based on performance comparisons of LR, EGB, and RF algorithms
Wadi El-Matulla, located in the eastern desert of Egypt, is the most important water basin. The Qift–Qusayr highway (west–east direction) and the...
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Integration of RS-GIS with Frequency Ratio, Fuzzy Logic, Logistic Regression and Decision Tree Models for Flood Susceptibility Prediction in Lower Gangetic Plain: A Study on Malda District of West Bengal, India
Flood is one of the most commonly occurring natural calamities in the lower Gangetic flood plain region of India. Hence, the present study aims to...
