System and method for modeling non-stationary time series using a non-parametric demand profile
US7580852B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 23, 2005 |
| Grant date | Aug 25, 2009 |
| Priority date | — |
| Expiry date | Mar 31, 2027 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q40/00
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
A non-stationary time series model using a likelihood function as a function of input data, base demand parameters, and time dependent parameter. The likelihood function may represent any statistical distribution. The likelihood function uses a prior probability distribution to provide information external to the input data and is used to control the model. In one embodiment the prior is a function of adjacent time periods of the demand profile. The base demand parameters and time dependent parameter are solved using a multi-diagonal band matrix. The solution of base demand parameters and time dependent parameter involves making estimates thereof in an iterative manner until the base demand parameters and time dependent parameter each converge. A non-stationary time series model is provided from an expression using the solution of the base demand parameters and time dependent parameter. The non-stationary time series model provides a demand forecast as a function of time.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.