In the new electricity market, the accurate electricity demand prediction can make high possible profit. However, electricity consumption data exhibits nonlinearity, high volatility, and susceptibility to various factors. Most existing prediction schemes inadequately account for these traits, resulting in weak performance. In view of this, we propose a collaborative multi-component optimization model (MCO-BHPSF) to achieve high accuracy electricity demand prediction. For this model, the original data is first decomposed into linear trend components and nonlinear residual components using the M...
