Method for predicting available parking space occupancy of parking lot in short time

The invention discloses a method for predicting the available parking space occupancy of a parking lot in a short time. The method comprises the following steps of: performing multi-resolution and N-scale decomposition on the time sequence c0 of the available parking space occupancy by using a wavelet function so as to obtain a low-frequency coefficient vector cN of which the scale is N and N high-frequency coefficient vectors d1, d2, ..., dN with different scales; reconstructing the low-frequency coefficient vector cN and the high-frequency coefficient vectors d1, d2, ..., dN so as to obtain N+1 time sequences CN, D1, D2, ..., DN; and establishing a weighted Markov chain prediction model for predicting to obtain N+1 prediction results and accumulating the N+1 prediction results so as to obtain a prediction result which corresponds to the original available parking space occupancy. A wavelet analysis-weighted Markov combined prediction model is provided according to the short-time change characteristic of the available parking space occupancy of the parking lot, so that convergence rate is increased, and a network parameter and a training parameter are easy to determine.