Comparing linear and nonlinear forecasts for Taiwan's electricity consumption

By H. Pao. 2006

149 citations recorded by the source corpus.

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Forecast of electricity consumption and economic growth in Taiwan by state space modeling (2009, methodology): “On the other hand, the multivariate models of neural network techniques [29,30], regression and econometric approach [31–33] have been also applied in predicting EC.”
Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption (2008, background): “Pao [12] presents a comparison of several linear and non-linear models including ANN models for forecast building energy consumption in Taiwan.”
The impact of energy consumption on economic growth: Evidence from linear and nonlinear models in Taiwan (2007, background): “Third, we should refer to the critical issue proposed by Pao [43], who found that Taiwan’s energy consumption has risen sharply because of rapid economic growth and higher living standards.”
Machine learning in energy economics and finance: A review (2019, background): “Many papers (e.g. Pao (2006), Azadeh et al. (2008), Lai et al. (2008), Ardakani and Ardehali (2014), and Castelli et al. (2015)) have built hybrid models to predict low-frequency energy demand trends in different countries.”