CMAQ-CNN: A new-generation of post-processing techniques for chemical transport models using deep neural networks
Chemical transport models simulate ambient air pollution concentrations by considering
emission, transport and deposition mechanism, and other physical processes. Despite their …
emission, transport and deposition mechanism, and other physical processes. Despite their …
Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system
As the deep learning algorithm has become a popular data analysis technique, atmospheric
scientists should have a balanced perception of its strengths and limitations so that they can …
scientists should have a balanced perception of its strengths and limitations so that they can …
JOHAN: a joint online hurricane trajectory and intensity forecasting framework
Hurricanes are one of the most catastrophic natural forces with potential to inflict severe
damages to properties and loss of human lives from high winds and inland flooding …
damages to properties and loss of human lives from high winds and inland flooding …
Applications of Deep Learning in Atmospheric Sciences: Air Quality Forecasting, Post-Processing, and Hurricane Tracking
E Eslami - 2020 - search.proquest.com
This study employs deep learning-based models for developing: fast, real-time air quality
forecasting systems; a post-processing tool for bias-correcting the chemical transport model; …
forecasting systems; a post-processing tool for bias-correcting the chemical transport model; …
[图书][B] Online Learning Algorithms for Mining Trajectory Data and Their Applications
D Wang - 2021 - search.proquest.com
Trajectories are spatio-temporal data that represent traces of moving objects, such as
humans, migrating animals, vehicles, and tropical cyclones. In addition to the geo-location …
humans, migrating animals, vehicles, and tropical cyclones. In addition to the geo-location …