Method and system for synthetic generation of time series data
First Claim
1. A system for generating synthetic data, comprising:
- one or more memory units storing instructions; and
one or more processors that execute the instructions to perform operations comprising;
receiving a dataset comprising time series data having a plurality of dimensions;
generating a transformed dataset by performing a first data transformation on the dataset, the first data transformation comprising a time-based data processing operation;
generating a first synthetic transformed dataset by implementing a data model using the transformed dataset, the data model being configured to generate synthetic transformed data based on a relationship between data of at least two dimensions of the transformed dataset;
generating a second synthetic transformed dataset by performing a second data transformation on the first synthetic transformed dataset, the second data transformation comprising an inverse of the first data transformation;
receiving a plurality of sample datasets having a plurality of respective dimensions;
generating a plurality of transformed sample datasets corresponding to the sample datasets by performing the first data transformation on the sample datasets; and
training the data model to generate synthetic transformed data based on the transformed sample datasets.
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Abstract
Systems and methods for generating synthetic data are disclosed. For example, a system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving a dataset that includes time series data having a plurality of dimensions and generating a transformed dataset by performing a first data transformation. The first data transformation may include a time-based data processing method. The operations may include generating a synthetic transformed-dataset by implementing a data model using the transformed dataset. The data model may be configured to generate synthetic transformed-data based on a relationship between data of at least two dimensions of the transformed dataset. The operations may include generating a synthetic dataset by performing a second data transformation on the synthetic transformed-dataset. The second data transformation may include an inverse of the first data transformation.
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Citations
19 Claims
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1. A system for generating synthetic data, comprising:
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one or more memory units storing instructions; and one or more processors that execute the instructions to perform operations comprising; receiving a dataset comprising time series data having a plurality of dimensions; generating a transformed dataset by performing a first data transformation on the dataset, the first data transformation comprising a time-based data processing operation; generating a first synthetic transformed dataset by implementing a data model using the transformed dataset, the data model being configured to generate synthetic transformed data based on a relationship between data of at least two dimensions of the transformed dataset; generating a second synthetic transformed dataset by performing a second data transformation on the first synthetic transformed dataset, the second data transformation comprising an inverse of the first data transformation; receiving a plurality of sample datasets having a plurality of respective dimensions; generating a plurality of transformed sample datasets corresponding to the sample datasets by performing the first data transformation on the sample datasets; and training the data model to generate synthetic transformed data based on the transformed sample datasets. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
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18. A method for generating synthetic data, the method comprising:
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receiving a dataset comprising time series data having a plurality of dimensions; generating a transformed dataset by performing a first data transformation on the dataset, the first data transformation comprising a time-based data processing operation; generating a first synthetic transformed-dataset by implementing a data model using the transformed dataset, the data model being configured to generate synthetic transformed-data based on a relationship between data of at least two dimensions of the transformed dataset; and generating a second synthetic transformed dataset by performing a second data transformation on the first synthetic transformed-dataset, the second data transformation comprising an inverse of the first data transformation; receiving a plurality of sample datasets having a plurality of respective dimensions; generating a plurality of transformed sample-datasets corresponding to the sample datasets by performing the first data transformation on the sample datasets; and training the data model to generate synthetic transformed-data based on the transformed sample-datasets.
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19. A system for generating synthetic data, comprising:
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one or more memory units storing instructions; and one or more processors that execute the instructions to perform operations comprising; receiving, at a server, from a client device, a dataset comprising numeric time-series data having a plurality of dimensions; generating a transformed dataset by performing a first data transformation on the dataset, the first data transformation comprising subtracting data associated with a first time point from data associated with a second time point; generating a synthetic transformed-dataset by implementing a data model using the transformed dataset, the data model comprising an RNN-CNN model configured to generate synthetic transformed-data based on a relationship between data of at least two dimensions of the transformed dataset; generating a synthetic dataset by performing a second data transformation on the synthetic transformed-dataset, the second data transformation comprising an inverse of the first data transformation; and transmitting, to the client device, the synthetic dataset.
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Specification