Forecasting events by modeling time series data

A computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform a process for making predictions based on time series data using one or more automatically selected prediction models, the process comprising:

• traversing a directed graph that comprises nodes corresponding to simulations;
• selecting nodes of the directed graph,
• wherein the directed graph specifies dependencies between the simulations such that a particular simulation, corresponding to a particular node with one or more incoming edges, is to be selected for performance when one or more previous simulations, corresponding to one or more previous nodes connected to the one or more incoming edges for the particular node, are complete, and
• wherein, for each selected node, a simulation corresponding to the selected node is performed by:
• obtaining a time series data set for the corresponding simulation;
• automatically selecting one or more top performing models, from a set of available prediction models, for the time series data set by:
• dividing the time series data into multiple sections;
• applying each of the available prediction models to a first of the multiple sections to generate first predictions for each model;
• determining a first accuracy score for each of the available prediction models based on a comparison of the first predictions from each of the available prediction models to the values in a second of the multiple sections;
• and
• selecting the one or more top performing models based, at least in part, on the first accuracy scores;
• generating multiple predictions for the corresponding simulation by applying the selected one or more top performing models to a version of the time series data set;
• and
• causing a user interface (UI) to be displayed including a representation of at least some of the multiple predictions generated for the corresponding simulations.

A computing system for making predictions based on time series data using one or more automatically selected prediction models, the computing system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the computing system to perform a process comprising:
• traversing a directed graph that comprises nodes corresponding to simulations;
• selecting nodes of the directed graph,
• wherein the directed graph specifies dependencies between the simulations such that a particular simulation, corresponding to a particular node with one or more incoming edges, is to be selected for performance when one or more previous simulations, corresponding to one or more previous nodes connected to the one or more incoming edges for the particular node, are complete, and
• wherein, for each selected node, a simulation corresponding to the selected node is performed by:
• obtaining a time series data set for the corresponding simulation;
• automatically selecting one or more top performing models, from a set of available prediction models, for the time series data set by:
• dividing the time series data into multiple sections;
• applying each of the available prediction models to a first of the multiple sections to generate first predictions for each model;
• determining a first accuracy score for each of the available prediction models based on a comparison of the first predictions from each of the available prediction models to the values in a second of the multiple sections;
• and
• selecting the one or more top performing models based, at least in part, on the first accuracy scores;
• generating multiple predictions for the corresponding simulation by applying the selected one or more top performing models to a version of the time series data set;
• and
• causing a user interface (UI) to be displayed including a representation of at least some of the multiple predictions generated for the corresponding simulations.