Flood prediction using machine learning models: Literature review
Floods are among the most destructive natural disasters, which are highly complex to model.
The research on the advancement of flood prediction models contributed to risk reduction …
The research on the advancement of flood prediction models contributed to risk reduction …
Machine learning in tropical cyclone forecast modeling: A review
Tropical cyclones have always been a concern of meteorologists, and there are many
studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting …
studies regarding the axisymmetric structures, dynamic mechanisms, and forecasting …
[HTML][HTML] Flood susceptibility mapping 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.
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Mapping flood-prone areas is an important part of flood disaster management. In this study …
Floating offshore wind turbines: Current status and future prospects
Offshore wind energy is a sustainable renewable energy source that is acquired by
harnessing the force of the wind offshore, where the absence of obstructions allows the wind …
harnessing the force of the wind offshore, where the absence of obstructions allows the wind …
Exploring deep learning capabilities for surge predictions in coastal areas
To improve coastal adaptation and management, it is critical to better understand and
predict the characteristics of sea levels. Here, we explore the capabilities of artificial …
predict the characteristics of sea levels. Here, we explore the capabilities of artificial …
A reliable hybrid outlier robust non-tuned rapid machine learning model for multi-step ahead flood forecasting in Quebec, Canada
I Ebtehaj, H Bonakdari - Journal of Hydrology, 2022 - Elsevier
Reliable and accurate flood forecasting is a complex and challenging problem that is
essential for the creation of disaster preparedness plans to protect life and reduce economic …
essential for the creation of disaster preparedness plans to protect life and reduce economic …
Short-term probabilistic prediction of significant wave height using bayesian model averaging: Case study of chabahar port, Iran
Accurate predictions of significant wave heights are important for a number of maritime
applications, such as design of coastal and offshore structures. In the present study, an …
applications, such as design of coastal and offshore structures. In the present study, an …
Machine learning in coastal bridge hydrodynamics: a state-of-the-art review
Coastal bridges are vulnerable to complicated hydrodynamics induced by hostile natural
hazards, relevant research is thus required to ensure the safe operation of these critical …
hazards, relevant research is thus required to ensure the safe operation of these critical …
Forecasting wind waves in the US Atlantic Coast using an artificial neural network model: Towards an AI-based storm forecast system
Z Wei - Ocean Engineering, 2021 - Elsevier
This study presents an artificial intelligence (AI) model to forecast time-series wind waves in
the US Atlantic Coast. The fundamental technique in the proposed model is the Long Short …
the US Atlantic Coast. The fundamental technique in the proposed model is the Long Short …
Application of GIS and machine learning to predict flood areas in Nigeria
Floods are one of the most devastating forces in nature. Several approaches for identifying
flood-prone locations have been developed to reduce the overall harmful impacts on …
flood-prone locations have been developed to reduce the overall harmful impacts on …