Patent ID: 11948065
Assignee: CITIGROUP TECHNOLOGY, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 1:
2. A method for responding to predicted events in time-series data using artificial intelligence models trained on non-homogenous time-series data, the method comprising:
generating a user profile for a user by:
receiving a first data set comprising a current state characteristic for a first system state; and
receiving a required future state characteristic for the first system state;

generating a synthetic profile for the user based on historical time-series data by:
receiving the historical time-series data;
training, using the historical time-series data, a second model using unsupervised learning, wherein the second model comprises a convolutional neural network; and
selecting, using the second model, a second data set from a plurality of available datasets based on similarities between state characteristics for the second data set and the current state characteristic and the required future state characteristic, wherein the second data set comprises second rate-of-change data over a second time period;
comparing the second rate-of-change data to a threshold rate of change to detect a rate-of-change event;
generating a normalized rate-of-change event by normalizing the rate-of-change event based on the first data set; and

using the synthetic profile to generate a recommendation for the user by:
inputting the first data set into a first model to generate first rate-of-change data over a first time period for the first system state;
generating modified first rate-of-change data based on the normalized rate-of-change event; and
generating for display, on a user interface, the recommendation based on the modified first rate-of-change data.