Research on Chaos Feature and Forecasting of Air Conditioning Load

Evolution law on air conditioning load is affected by many factors which are very difficult to be known and gained, that which results in low precision of simulation and forecast. Based on analysis on chaos characteristic of air conditioning load time series, BP neural networks model based on chaos phase space is proposed to forecast air conditioning load through embedding dimension. Considering influence of dynamical factor of air conditioning load as well as difficulty of calculating number of input cell, the model is provided with strong nonlinear mapping capacity, is applied to simulate and forecast air conditioning load, the outcomes is reasonable and higher precision.