Approach for generating time series datasets based on symbolic representation of data and cloud model

In order to generate reliable synthetic datasets,this paper proposed a method based on the symbolic representation of the original data and cloud model. Firstly,the original data or the knowledge about the data( we often can only get the knowledge of the domain) was symbolic represented with the SFVS algorithm,and then generated synthetic dataset by using the symbolic vector as input by the cloud model. Simulation experiments demonstrate that the characters and the connotative knowledge of the synthetic data set are the same as the original data’s,moreover,the randomicity as well as the complexity of the synthetic data set is controllable.