Exploring machine learning potential for climate change risk assessment
Global warming is exacerbating weather, and climate extremes events and is projected to
aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering …
aggravate multi-sectorial risks. A multiplicity of climate hazards will be involved, triggering …
A practical approach to flood hazard, vulnerability, and risk assessing and map** for Quang Binh province, Vietnam
Flood damage is often severe and directly affects housing, transport infrastructure, industrial,
service, commercial, and land use. A flood risk assessment based on vulnerability indicators …
service, commercial, and land use. A flood risk assessment based on vulnerability indicators …
[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 …
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 …
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 …
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 …
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 …
A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility map**
Flash flood is a typical natural hazard that occurs within a short time with high flow velocities
and is difficult to predict. In this study, we propose and validate a new soft computing …
and is difficult to predict. In this study, we propose and validate a new soft computing …
Modeling flood susceptibility using data-driven approaches of naïve bayes tree, alternating decision tree, and random forest methods
Floods are one of the most devastating types of disasters that cause loss of lives and
property worldwide each year. This study aimed to evaluate and compare the prediction …
property worldwide each year. This study aimed to evaluate and compare the prediction …
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 …