Abstract: The present invention describes systems and methods for facilitating digital voting. It is an object of the present invention to provide a secure digital system wherein voters' identities can be verified and can verify that their votes are recorded correctly. Additionally, this digital voting system reduces the cost and time required for traditional elections. This digital voting system and method comprises online registration, an online voting platform, secured vote encryption, and voter results verification.

Abstract: Updating a prediction model, where the prediction model is used for time series data, a computer selects a first prediction time window in an order from a plurality of prediction time windows associated with the prediction model, and predicts predicted values of the time series data at time points within the first prediction time window. The computer calculates a prediction error associated with the first prediction time window based on the one or more predicted values and one or more actual measured values of the time series data at the plurality of time points. The computer determines whether the prediction error is larger than a predefined error threshold associated with the first prediction time window, and in response to determining the prediction error is larger than the predefined error threshold, provides a notification of updating the prediction model.

Abstract: In an approach to updating a prediction model, where the prediction model is used for time series data, a computer selects a first prediction time window in an order from a plurality of prediction time windows associated with the prediction model, and predicts one or more predicted values of the time series data at a plurality of time points within the first prediction time window. The computer calculates a prediction error associated with the first prediction time window based on the one or more predicted values and one or more actual measured values of the time series data at the plurality of time points. The computer determines whether the prediction error is larger than a predefined error threshold associated with the first prediction time window, and in response to determining the prediction error is larger than the predefined error threshold, provides a notification of updating the prediction model.