A novel hybrid artificial intelligence approach for flood susceptibility assessment
A new artificial intelligence (AI) model, called Bagging-LMT-a combination of bagging
ensemble and Logistic Model Tree (LMT)-is introduced for mapping flood susceptibility. A …
ensemble and Logistic Model Tree (LMT)-is introduced for mapping flood susceptibility. A …
Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic …
Preparation of landslide susceptibility maps is considered as the first important step in
landslide risk assessments, but these maps are accepted as an end product that can be …
landslide risk assessments, but these maps are accepted as an end product that can be …
Novel hybrid evolutionary algorithms for spatial prediction of floods
Adaptive neuro-fuzzy inference system (ANFIS) includes two novel GIS-based ensemble
artificial intelligence approaches called imperialistic competitive algorithm (ICA) and firefly …
artificial intelligence approaches called imperialistic competitive algorithm (ICA) and firefly …
Prediction of landslide susceptibility in Rudraprayag, India using novel ensemble of conditional probability and boosted regression tree-based on cross-validation …
The present research examines the landslide susceptibility in Rudraprayag district of
Uttarakhand, India using the conditional probability (CP) statistical technique, the boost …
Uttarakhand, India using the conditional probability (CP) statistical technique, the boost …
Landslide detection and susceptibility mapping by airsar data using support vector machine and index of entropy models in cameron highlands, malaysia
Since landslide detection using the combination of AIRSAR data and GIS-based
susceptibility mapping has been rarely conducted in tropical environments, the aim of this …
susceptibility mapping has been rarely conducted in tropical environments, the aim of this …
A novel hybrid approach of bayesian logistic regression and its ensembles for landslide susceptibility assessment
A novel artificial intelligence approach of Bayesian Logistic Regression (BLR) and its
ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was …
ensembles [Random Subspace (RS), Adaboost (AB), Multiboost (MB) and Bagging] was …
Landslide susceptibility assessment at the Wuning area, China: A comparison between multi-criteria decision making, bivariate statistical and machine learning …
The aim of this research is to investigate multi-criteria decision making [spatial multi-criteria
evaluation (SMCE)], bivariate statistical methods [frequency ratio (FR), index of entropy …
evaluation (SMCE)], bivariate statistical methods [frequency ratio (FR), index of entropy …
Automated heart sound activity detection from PCG signal using time–frequency-domain deep neural network
The phonocardiogram (PCG) signal deciphers the mechanical activity of the heart, and it
consists of the fundamental heart sounds (FHSs)(S1 and S2), murmurs, and other …
consists of the fundamental heart sounds (FHSs)(S1 and S2), murmurs, and other …
Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula
This work explores the use of different seismicity indicators as inputs for artificial neural
networks. The combination of multiple indicators that have already been successfully used …
networks. The combination of multiple indicators that have already been successfully used …
Insights into the Effects of Co-Regulated Factors on Li1.3Al0.3Ti1.7(PO4)3 Solid Electrolyte Preparation: Sources, Calcination Temperatures, and Sintering …
C Luo, Q Shuai, G Zhao, M Zhang, B Wu… - … Applied Materials & …, 2023 - ACS Publications
The ionic conductivity, phase components, and microstructures of LATP depend on its
synthesis process. However, their relative importance and their interactions with synthesis …
synthesis process. However, their relative importance and their interactions with synthesis …