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20152021
most citedTourism Demand Forecasting: An Ensemble Deep Learning Approach

4 citations · 9 across the 7 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

physics.soc-ph2020★ 1 cited

Knowledge Mapping in Electricity Demand Forecasting: A Scientometric Insight

Dongchuan Yang, Ju-e Guo, Jie Li +2

Forecasting electricity demand plays a fundamental role in the operation and planning procedures of power systems and the publications about electricity demand forecasting increasi…

cs.DL2020★ 1 cited

New Research Trends in Unconventional Oil and Gas Environmental Issue: A Bibliometric Analysis

Dan Bi, Ju-e Guo, Shouyang Wang +1

With the booming of unconventional gas production in the world, how to balance environment pollution risk and economy of unconventional gas have become a common dilemma around the…

stat.AP2020★ 1 cited

Seasonal and Trend Forecasting of Tourist Arrivals: An Adaptive Multiscale Ensemble Learning Approach

Shaolong Suna, Dan Bi, Ju-e Guo +1

The accurate seasonal and trend forecasting of tourist arrivals is a very challenging task. In the view of the importance of seasonal and trend forecasting of tourist arrivals, and…

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…

stat.AP2020★ 4 cited

Tourism Demand Forecasting: An Ensemble Deep Learning Approach

Shaolong Sun, Yanzhao Li, Ju-e Guo +1

The availability of tourism-related big data increases the potential to improve the accuracy of tourism demand forecasting, but presents significant challenges for forecasting, inc…