قائمة الطعام
Landslide is one of the most serious and widespread disasters in natural disasters, which seriously endangers the lives and property of residents. Based on the occurrence mechanism of landslide, this paper uses the analytic hierarchy process-comprehensive index (AHP-CI) model and takes Yuan'an County in China as an …
Table 1 shows that the basic topographic and geological maps of the 1:50,000 scale and the landslide disaster map of 1:10,000 scale, DEM data and remote sensing data with resolution of 30 m. The ...
ABSTRACT . This study selected ten condition factors from the perspectives of topography, geological structure, hydrology and human for min- ing subsidence mapping by two types of models (knowledge- driven model and data-driven model) by taking Jining City, China …
Evaluating the landslide susceptibility in Zhenping County using a hybrid of support vector regression with grey wolf optimizer and firefly algorithm by frequency ratio (FR) preprocessed shows that the SVR-GWO model has the best performance in landslide spatial prediction and all three models have good prospects for regional-scale landslide …
Flash floods are a significant threat to arid and semi-arid regions, causing considerable loss of life and damage, including roads, bridges, check dams and dikes, reservoir filling, and mudslides in populated areas as well as agricultural fields. Flood risk is a complex process linked to numerous morphological, pedological, geological, anthropic, …
The purpose of the present study is to predict and draw up non-grain cultivated land (NCL) susceptibility map based on optimized Extreme Gradient Boosting (XGBoost) model using the Particle Swarm ...
The purpose of the present study is to predict and draw up non-grain cultivated land (NCL) susceptibility map based on optimized Extreme Gradient Boosting (XGBoost) model using the Particle Swarm...
susceptibility evaluation can be made using a CPT-based approach, relating the measured cone resistance to the cyclic shear stress ratio [7,8]. Flow liquefaction, however, received much less attention, despite the recognition of risks in …
ORIGINAL PAPER Debris-flow susceptibility analysis using fluvio-morphological parameters and data mining: application to the Central-Eastern Pyrenees ... are largely unacceptable. 6.3 Susceptibility maps Results are previously reported in terms of performance and other ratios. Susceptibility assessments are not easily used and …
Susceptibility weighted imaging (SWI) is a routine magnetic resonance imaging (MRI) sequence that combines the magnitude and high-pass filtered phase images to qualitatively enhance the image contrasts related to tissue susceptibility. ... Tremendous amounts of the high-pass filtered phase data with low signal to noise ratio and incomplete ...
The second phase was to use the Frequency Ratio (FR) method to quantify the level of involvement of the factors in the slides. The method of FR in landslides susceptibility analysis has been in use for quite some time now (Yan et al. Citation 2019). Could be the first researchers to have reported the use of the technique for landslides …
In this study, two GIS-based analytical methods, Frequency ratio (FR) and Shannon Entropy (SE), were evaluated for the mapping of the Chamoli region in Uttarakhand, India, for estimating the area's landslide susceptibility. There is a lot of on-going and proposed infrastructure projects in the area due to which, there is a surge in …
This study aims to demarcate landslide susceptible zones using methods of analytical hierarchy process (AHP) and frequency ratio (FR) to find the most influencing factors and to compare their prediction capability. Ten causative factors (slope angle, elevation, lithology, land use/land cover types, normalized difference moisture index, …
Abstract: Susceptibility weighted imaging (SWI) is a routine magnetic resonance imaging (MRI) sequence that combines the magnitude and high-pass filtered phase images to qualitatively enhance the image contrasts related to tissue susceptibility. Tremendous amounts of the high-pass filtered phase data with low signal to noise ratio …
In recent years landslides occurred in the Fushun West open-pit mining area compared with previous ones show obvious temporal and spatial variations in the scale, activity frequency and spatial position, followed up by changes in landslide susceptibility, which presents new challenges for future treatment. We compared susceptibility …
The main aim of this study was to apply and compare two GIS-based data mining models, namely support vector machine (SVM) by four kernel functions (linear-SVM, polynomial-SVM, radial basic function-SVM, and sigmoidal-SVM) and entropy models in landslide susceptibility mapping, in Shangzhou District, China. Initially, 145 landslide …
Mining activity at Taxco produces seven mining waste deposits, which are problematic for the health of the community and for the environment in general. This study targets the Guerrero I mining waste dam (the youngest of the region), located south of Taxco de Alarcon, in the northern portion of Guerrero State, Mexico. This study reports …
In this study, we employed three state-of-the art data mining techniques for landslide susceptibility mapping in the Longhai area of China. The RF and NBTree models have been used in many landslide susceptibility studies (particularly the RF model), but investigation of the BFTree model has rarely been conducted in landslide modeling.
Susceptibility models have been developed analyzing the statistical relationships between the cavity sections with evidence of instability and a number of predisposing factors mainly related to the 3D geometry of the voids, roof thickness and …
Positive state parameter values characterize a contractive response during shearing and, for non-plastic soils, can indicate flow liquefaction susceptibility. This paper presents a methodology to classify and estimate the state parameter ( Ψ) for non …
The spatial prediction of landslide susceptibility is an important prerequisite for the analysis of landslide hazards and risks in any area. This research uses three data mining techniques, such as an adaptive neuro-fuzzy inference system combined with frequency ratio (ANFIS-FR), a generalized additive model (GAM), and a support vector …
Landslides caused countless economic and casualty losses in China, especially in mountainous and hilly areas. Landslide susceptibility mapping is an important approach and tool for landslide disaster prevention and control. This study presents a landslide susceptibility assessment using frequency ratio (FR) and index of entropy (IOE) …
Low susceptibility covered 1406.7 km 2 area in the conventional frequency ratio map, 1923.3 km 2 in the modified frequency ratio model map and 1156.3 km 2 area in the support vector machine map (Fig. 6 and Table 1). Very high and high susceptibility was found in the core areas of the SBR (southern part) and some areas adjacent to …
Landslide Susceptibility Mapping (LSM) is a commonly employed approach for predicting the spatial distribution and probability of landslides. LSM outcomes are crucial for reducing landslide...
Therefore, this factor simultaneously considers the effects of depth and the proximity of mined panels on mining subsidence susceptibility. ... Yilmaz I (2009) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat-Turkey). …
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WEBThis study shows that most of the very high susceptibility areas of deforestation are close to mining and agricultural surrounding forest compartments sites. Also, these forest compartments show very high susceptibility to deforestation in …
Assessing subsidence susceptibility to coal mining using frequency ratio, statistical index and Mamdani fuzzy models: evidence from Raniganj coalfield, India
From the results, it can be seen that the mining area density, land use, and groundwater burial conditions are the most important index factors affecting mining subsidence susceptibility. Combined with AHP, FR-EWM and FR-FCE methods, the …
The qualitative landslide susceptibility analysis was carried out by a combination of frequency ratio analyses and a heuristic iterative index-based method using a Geographical Information System. As conditioning factors, the parameters lithology, slope angle, -aspect, -curvature, drainage buffer distance and land use were applied.
The aim of this study was to evaluate and compare landslide susceptibility maps produced using the random forest (RF) data mining technique with those produced by bivariate (evidential belief function and frequency ratio) and multivariate (logistic regression) statistical models for Lianhua County, China.
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