Early detection of earthquakes using iot and cloud infrastructure: A survey
Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a …
Map** the landscape and roadmap of geospatial artificial intelligence (GeoAI) in quantitative human geography: An extensive systematic review
This paper brings a comprehensive systematic review of the application of geospatial
artificial intelligence (GeoAI) in quantitative human geography studies, including the …
artificial intelligence (GeoAI) in quantitative human geography studies, including the …
Influence of data splitting on performance of machine learning models in prediction of shear strength of soil
The main objective of this study is to evaluate and compare the performance of different
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
machine learning (ML) algorithms, namely, Artificial Neural Network (ANN), Extreme …
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility map**
This study introduces four heterogeneous ensemble-learning techniques, that is, stacking,
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
blending, simple averaging, and weighted averaging, to predict landslide susceptibility in …
Flood detection and susceptibility map** using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based …
Map** flood-prone areas is a key activity in flood disaster management. In this paper, we
propose a new flood susceptibility map** technique. We employ new ensemble models …
propose a new flood susceptibility map** technique. We employ new ensemble models …
Shallow landslide susceptibility map**: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …
and can cause social upheaval and loss of life. As a result, many scientists study the …
Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran
Earthquakes are natural phenomena, which induce natural hazard that seriously threatens
urban areas, despite significant advances in retrofitting urban buildings and enhancing the …
urban areas, despite significant advances in retrofitting urban buildings and enhancing the …
GIS-based machine learning algorithms for gully erosion susceptibility map** in a semi-arid region of Iran
In the present study, gully erosion susceptibility was evaluated for the area of the Robat Turk
Watershed in Iran. The assessment of gully erosion susceptibility was performed using four …
Watershed in Iran. The assessment of gully erosion susceptibility was performed using four …
Spatial prediction of landslide susceptibility using gis-based data mining techniques of anfis with whale optimization algorithm (woa) and grey wolf optimizer (gwo)
The most dangerous landslide disasters always cause serious economic losses and human
deaths. The contribution of this work is to present an integrated landslide modelling …
deaths. The contribution of this work is to present an integrated landslide modelling …
[HTML][HTML] Deep learning neural networks for spatially explicit prediction of flash flood probability
Flood probability maps are essential for a range of applications, including land use planning
and develo** mitigation strategies and early warning systems. This study describes the …
and develo** mitigation strategies and early warning systems. This study describes the …