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Combination forecasting of energy demand in the UK
Marco Barassi
, Yuqian Zhao
Economics
Research output
:
Contribution to journal
›
Article
›
peer-review
2
Citations (Scopus)
73
Downloads (Pure)
Overview
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Dive into the research topics of 'Combination forecasting of energy demand in the UK'. Together they form a unique fingerprint.
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Weight
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Business & Economics
Model Averaging
100%
Energy Demand
59%
Jackknife
40%
Individual Model
27%
Forecast Error
23%
Vector Autoregression
21%
Bayesian Model Averaging
14%
Multivariate Models
13%
Demand Response
13%
Neural Networks
13%
Electricity Generation
13%
Demand Forecasting
12%
Electricity Price
11%
Smoothing
11%
Weighting
10%
Electricity
9%
Prediction
8%
Purchasing
8%
Energy
8%
Performance
4%
Industry
3%
Engineering & Materials Science
Electricity
10%
Mean square error
8%
Electric industry
7%
Purchasing
5%
Coal
3%
Neural networks
2%