Forecasting with state transitions and confidence factors

A computer-implemented method, comprising:

• segmenting, by a device comprising a processor, data associated with one or more assets to determine a set of classifications for one or more attributes related to the one or more assets;
• generating, by the device, a state machine associated with a stochastic model based on the set of classifications for the data;
• performing, by the device, a machine learning process associated with the state machine to determine one or more behavior changes associated with the one or more attributes related to the one or more assets;
• predicting, by the device and based on the one or more behavior changes associated with the one or more attributes related to the one or more assets, a change in demand data for the one or more assets during a future interval of time;
• and
• configuring, by the device, a state of the state machine with a first classification related to demand for the one or more assets, a second classification related to value for the one or more assets, and a third classification related to availability for the one or more assets.

A non-transitory computer-readable medium comprising at least one computer-readable storage medium having program instructions embodied thereon, the program instructions executable by a processor to cause the processor to:

• segment data associated with one or more assets to determine a set of classifications for one or more attributes related to the one or more assets;
• generate a state machine associated with a stochastic model based on the set of classifications for the data;
• perform a machine learning process associated with the state machine to determine one or more behavior changes associated with the one or more attributes related to the one or more assets;
• predict, based on the one or more behavior changes associated with the one or more attributes related to the one or more assets, a change in demand data for the one or more assets during a future interval of time;
• and
• configure a state of the state machine with a first classification related to demand for the one or more assets, a second classification related to value for the one or more assets, and a third classification related to availability for the one or more assets.