Abstract: Systems and methods for forecasting recurring anomalies in time series data include determining forecast data from historical data of time series data where the forecast data is for a desired future time span; combining the forecast data with the historical data to form a combined time series; determining a normal operating range using the combined time series; detecting anomalies in the forecast data based on the normal operating range; and providing an output including the detected anomalies in the forecast data.

Abstract: Systems and methods for forecasting recurring anomalies in time series data include determining forecast data from historical data of time series data where the forecast data is for a desired future time span; combining the forecast data with the historical data to form a combined time series; determining a normal operating range using the combined time series; detecting anomalies in the forecast data based on the normal operating range; and providing an output including the detected anomalies in the forecast data.

Abstract: Systems and methods include managing a Network Digital Twin (NDT) for a network, the NDT including an emulation model and an optimization model, wherein the emulation model is configured to emulate the network and the optimization model is configured to determine configuration changes to the network based on a cost function; performing an iterative procedure with the optimization model and the emulation model to determine one or more configuration changes to the network based on the cost function; and providing the one or more configuration changes from the iterative procedure for use in the network, where the one or more configuration changes address the cost function.