Short-term building energy consumption prediction strategy based on modal decomposition and reconstruction algorithm

•A density clustering-based method is proposed to optimize time-series datasets.•Time-series decomposition method is applied to reduce the nonlinearity and non-stationary of the original data.•A more engineering energy consumption prediction modeling strategy is provided.•A neural network model optimized by a self-attention mechanism is presented for modeling.•A hybrid deep-machine learning model is used for prediction to reduce the prediction error.