PM2.5 Prediction Model Based on Combinational Hammerstein Recurrent Neural Networks

PM2.5 Prediction Model Based on Combinational Hammerstein Recurrent Neural Networks

Airborne particulate matter 2.5 (PM2.5) can have a profound effect on the health of the population. Many researchers have been reporting highly accurate numerical predictions based on raw PM2.5 data imported directly into deep learning models; however, there is still considerable room for improvemen...

Full description

Bibliographic Details
Main Authors: Yi-Chung Chen, Tsu-Chiang Lei, Shun Yao, Hsin-Ping Wang
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Mathematics
Subjects:
feature selection
recurrent neural networks
PM2.5 predictions
time series prediction
Online Access:https://www.mdpi.com/2227-7390/8/12/2178

Similar Items

Similar Items