[HTML][HTML] Artificial intelligence in agricultural map**: A review
Artificial intelligence (AI) plays an essential role in agricultural map**. It reduces costs and
time and increases efficiency in agricultural management activities, which improves the food …
time and increases efficiency in agricultural management activities, which improves the food …
Assessing the predictive capability of ensemble tree methods for landslide susceptibility map** using XGBoost, gradient boosting machine, and random forest
EK Sahin - SN Applied Sciences, 2020 - Springer
Decision tree-based classifier ensemble methods are a machine learning (ML) technique
that combines several tree models to produce an effective or optimum predictive model, and …
that combines several tree models to produce an effective or optimum predictive model, and …
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 …
Soft computing ensemble models based on logistic regression for groundwater potential map**
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
Performance evaluation of machine learning methods for forest fire modeling and prediction
Predicting and map** fire susceptibility is a top research priority in fire-prone forests
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …
worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB) …
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 …
Coupling RBF neural network with ensemble learning techniques for landslide susceptibility map**
Using multiple ensemble learning techniques for improving the predictive accuracy of
landslide models is an active research area. In this study, we combined a radial basis …
landslide models is an active research area. In this study, we combined a radial basis …
Landslide susceptibility map** using machine learning algorithms and remote sensing data in a tropical environment
We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an
ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands …
ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands …
[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 …
The main aim of this study is to assess groundwater potential of the DakNong province,
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …
Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates …