Abstract: A method and an apparatus for generating time series data based on multi-condition constraints, and a medium are provided. The method include the following: a data repair request from a client is received, the data repair request including to-be-repaired data and condition information; normalization processing is performed on the to-be-repaired data to obtain normalized data, and tensor processing is performed on the condition information to obtain a feature label; a trained data repair model is called to perform repair processing on the normalized data according to the feature label to obtain first repaired data, the data repair model being obtained by training according to sample data, a first sample condition, real sample data and a second sample condition, and the sample data being noise data; and the first repaired data is sent to the client.

Abstract: A method and an apparatus for generating time series data based on multi-condition constraints, and a medium are provided. The method include the following: a data repair request from a client is received, the data repair request including to-be-repaired data and condition information; normalization processing is performed on the to-be-repaired data to obtain normalized data, and tensor processing is performed on the condition information to obtain a feature label; a trained data repair model is called to perform repair processing on the normalized data according to the feature label to obtain first repaired data, the data repair model being obtained by training according to sample data, a first sample condition, real sample data and a second sample condition, and the sample data being noise data; and the first repaired data is sent to the client.