most citedA Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network

5 citations · 5 across the 2 of their papers we have counts for

collaborators

2 papers

eess.SP2020★ 5 cited

A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network

Fuxin Jiang, Chengyuan Zhang, Shaolong Sun +1

For hourly PM2.5 concentration prediction, accurately capturing the data patterns of external factors that affect PM2.5 concentration changes, and constructing a forecasting model…

econ.GN2020

A New Decomposition Ensemble Approach for Tourism Demand Forecasting: Evidence from Major Source Countries

Chengyuan Zhang, Fuxin Jiang, Shouyang Wang +1

The Asian-pacific region is the major international tourism demand market in the world, and its tourism demand is deeply affected by various factors. Previous studies have shown th…