Weight adjusted composite model for forecasting in anomalous environments

A computer program product for event forecasting in anomalous environments, the computer program product comprising:

• a computer readable storage medium;
• program instructions of a forecasting data processing system comprising a software-implemented predictive model configured to cause a processor to perform a simulation of a phenomenon to forecast outcomes of the phenomenon at a future time;
• program instructions, stored on the computer readable storage medium, to create new data of a composite forecasting model by combining with a base forecasting model a second forecasting model, the base forecasting model causing the processor to output a first forecast of an event in a time series, the data of the time-series comprising an anomalous portion, wherein the anomalous portion comprises a non-uniformity in a distribution of the event in the time-series, the second forecasting model being configured to represent the anomalous portion of data in the time series, wherein the second forecasting model comprises an equation whose curve fits, within a threshold, a curve formed by a set of values in the anomalous portion, and wherein the base forecasting model forecasts a value of the event in a non-anomalous portion of the data of the time series;
• program instructions, stored on the computer readable storage medium, to combine with the composite model a mixing algorithm, the mixing algorithm causing the processor to adjust a set of weights associated with the composite model;
• program instructions, stored on the computer readable storage medium, to adjust, by the processor, responsive to identifying a future period in which the event is to be forecasted, using the mixing algorithm, existing weight data of a subset of the set of weights to produce new weight data of the subset of the set of weights, the processor using the new weight data to convert the composite forecasting model to a weight adjusted composite model in the event forecasting data processing system;
• and
• program instructions, stored on the computer readable storage medium, to execute, using the processor and a memory, the weight adjusted composite model to output a second forecast of the event during the future period in the anomalous portion of the time-series, wherein the second forecast has a better accuracy relative to the first forecast.

A computer system for event forecasting in anomalous environments, the computer system comprising:

• a processor, a memory, and a computer-readable storage device;
• program instructions, stored on the computer-readable storage device for execution by the processor via the memory, the program instructions comprising:
• a forecasting data processing system comprising a software-implemented predictive model configured to cause the processor to perform a simulation of a phenomenon to forecast outcomes of the phenomenon at a future time;
• program instruction to create new data of a composite forecasting model by combining with a base forecasting model a second forecasting model, the base forecasting model causing the processor to output a first forecast of an event in a time series, the data of the time-series comprising an anomalous portion, wherein the anomalous portion comprises a non-uniformity in a distribution of the event in the time-series, the second forecasting model being configured to represent the anomalous portion of data in the time series, wherein the second forecasting model comprises an equation whose curve fits, within a threshold, a curve formed by a set of values in the anomalous portion, and wherein the base forecasting model forecasts a value of the event in a non-anomalous portion of the data of the time series;
• program instruction to combine with the composite model a mixing algorithm, the mixing algorithm causing the processor to adjust a set of weights associated with the composite model;
• program instruction to adjust, by the processor, responsive to identifying a future period in which the event is to be forecasted, using the mixing algorithm, existing weight data of a subset of the set of weights to produce new weight data of the subset of the set of weights, the processor using the new weight data to convert the composite forecasting model to a weight adjusted composite model in the event forecasting data processing system;
• and
• program instruction to execute, using the processor and the memory, the weight adjusted composite model to output a second forecast of the event during the future period in the anomalous portion of the time-series, wherein the second forecast has a better accuracy relative to the first forecast.