A hybrid CNN-LSTM model for typhoon formation forecasting
A typhoon is an extreme weather event that can cause huge loss of life and economic
damage in coastal areas and beyond. As a consequence, the search for more accurate …
damage in coastal areas and beyond. As a consequence, the search for more accurate …
Improving monthly rainfall forecast in a watershed by combining neural networks and autoregressive models
The main aim of the rain forecast is to determine rain occurrence conditions in a specific
location. This is considered of vital importance to assess the availability of water resources …
location. This is considered of vital importance to assess the availability of water resources …
Rapid intensification of tropical cyclones in the Gulf of Mexico is more likely during marine heatwaves
Tropical cyclones can rapidly intensify under favorable oceanic and atmospheric conditions.
This phenomenon is complex and difficult to predict, making it a serious challenge for …
This phenomenon is complex and difficult to predict, making it a serious challenge for …
Individual-level fatality prediction of COVID-19 patients using AI methods
The global covid-19 pandemic puts great pressure on medical resources worldwide and
leads healthcare professionals to question which individuals are in imminent need of care …
leads healthcare professionals to question which individuals are in imminent need of care …
Typhoon intensity forecasting based on LSTM using the rolling forecast method
S Yuan, C Wang, B Mu, F Zhou, W Duan - Algorithms, 2021 - mdpi.com
A typhoon is an extreme weather event with strong destructive force, which can bring huge
losses of life and economic damage to people. Thus, it is meaningful to reduce the …
losses of life and economic damage to people. Thus, it is meaningful to reduce the …
Graph Neural Network for spatiotemporal data: methods and applications
In the era of big data, there has been a surge in the availability of data containing rich spatial
and temporal information, offering valuable insights into dynamic systems and processes for …
and temporal information, offering valuable insights into dynamic systems and processes for …
A deep learning ensemble approach for predicting tropical cyclone rapid intensification
BF Chen, YT Kuo, TS Huang - Atmospheric Science Letters, 2023 - Wiley Online Library
Predicting rapid intensification (RI) of tropical cyclones (TCs) is critical in operational
forecasting. Statistical schemes rely on human‐driven feature extraction and predictor …
forecasting. Statistical schemes rely on human‐driven feature extraction and predictor …
Predicting the spatiotemporal characteristics of atmospheric rivers: A novel data-driven approach
Abstract Atmospheric Rivers (ARs) are narrow bands of high-water vapor content in the low
troposphere of mid-latitude regions through which most of the poleward moisture is being …
troposphere of mid-latitude regions through which most of the poleward moisture is being …
El Niño-Southern Oscillation forecasting using complex networks analysis of LSTM neural networks
Abstract Arguably, El Niño-Southern Oscillation (ENSO) is the most influential climatological
phenomenon that has been intensively researched during the past years. Currently, the …
phenomenon that has been intensively researched during the past years. Currently, the …
Cloud, edge, and mobile computing for smart cities
Smart cities evolve rapidly along with the technical advances in wireless and sensor
networks, information science, and human–computer interactions. Urban computing …
networks, information science, and human–computer interactions. Urban computing …