Pathways and challenges of the application of artificial intelligence to geohazards modelling
The application of artificial intelligence (AI) and machine learning in geohazard modelling
has been rapidly growing in recent years, a trend that is observed in several research and …
has been rapidly growing in recent years, a trend that is observed in several research and …
[HTML][HTML] Flood susceptibility modelling using advanced ensemble machine learning models
Floods are one of nature's most destructive disasters because of the immense damage to
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to …
Urban flood hazard assessment and management practices in south asia: a review
Urban flooding is a frequent disaster in cities. With the increasing imperviousness caused by
rapid urbanization and the rising frequency and severity of extreme events caused by …
rapid urbanization and the rising frequency and severity of extreme events caused by …
Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment
The main objective of the current study was to introduce a Deep Learning Neural Network
(DLNN) model in landslide susceptibility assessments and compare its predictive …
(DLNN) model in landslide susceptibility assessments and compare its predictive …
Improving prediction of water quality indices using novel hybrid machine-learning algorithms
River water quality assessment is one of the most important tasks to enhance water
resources management plans. A water quality index (WQI) considers several water quality …
resources management plans. A water quality index (WQI) considers several water quality …
Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method
Flash-floods are increasingly recognized as a frequent natural hazard worldwide. Iran has
been among the most devastated regions affected by the major floods. While the temporal …
been among the most devastated regions affected by the major floods. While the temporal …
[Retracted] Taxonomy of Adaptive Neuro‐Fuzzy Inference System in Modern Engineering Sciences
Adaptive Neuro‐Fuzzy Inference System (ANFIS) blends advantages of both Artificial Neural
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …
Networks (ANNs) and Fuzzy Logic (FL) in a single framework. It provides accelerated …
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 …
Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction map** in the Middle Ganga Plain, India
This study is an attempt to quantitatively test and compare novel advanced-machine
learning algorithms in terms of their performance in achieving the goal of predicting flood …
learning algorithms in terms of their performance in achieving the goal of predicting flood …
[HTML][HTML] Flood susceptibility map** using multi-temporal SAR imagery and novel integration of nature-inspired algorithms into support vector regression
Flood has long been known as one of the most catastrophic natural hazards worldwide.
Map** flood-prone areas is an important part of flood disaster management. In this study …
Map** flood-prone areas is an important part of flood disaster management. In this study …