In this article, a systematic literature review of 419 articles on energy demand modeling,
published between 2015 and 2020, is presented. This provides researchers with an …

A modified grey prediction model is employed to accurately forecast China's overall and
industrial electricity consumption. To this end, a novel optimized grey prediction model …

Despite growing urban electricity consumption, information on actual energy use in the
household sector is still limited and causal factors leading to electricity consumption remain …

The prediction of the spread of coronavirus disease 2019 (COVID-19) is vital in taking
preventive and control measures to reduce human health damage. The Grey Modelling (1 …

Research indicates that forecast combination is one of the most important and effective
approaches for time series forecasting. The success of forecast combination depends on …

To address the global challenge of climate change and achieve sustainable development,
decarbonizing the electric power system in China is considered the most imperative since …

This paper presents a method based on deep learning to deal with big data times series
forecasting. The deep feed forward neural network provided by the H2O big data analysis …

The remarkable prediction performance of electricity consumption has always assumed
particular importance for electric power utility planning and economic development. On …

Forecasting the residential electricity consumption can provide an effective and sustainable
electricity supply in the rapid development of urbanization and industrialization. However, it …

In the context of small sample and poor information, the data often change rapidly and
interact with multiple factors which make it a challenge to analyse and predict multivariate …