This paper proposes a new short-term combination prediction model of wind speed by means of ensemble empirical mode decomposition (EEMD) and improved extreme learning machine (IELM). Firstly, wind speed series is decomposed into several components with different frequency bands by EEMD to reduce the series non-stationary. Secondly, the phase space of each component is reconstructed in order to solve the randomness and component information lost of input dimensionality selection of extreme learning machine, and then an IELM model of each component is established. Finally, the forecast result of each component is superimposed to get the final result. The simulation result verifies that the hybrid model has higher prediction accuracy of wind speed.