EMD-Spectral Prediction (ESP)
First Claim
Patent Images
1. A computer-implemented method comprising:
- obtaining a time series, comprising real-world data over a specified period of time;
decomposing the time series into a superposition of a plurality of components;
for each one of the plurality of components, selecting a corresponding prediction algorithm;
generating a corresponding model for each of the plurality of components and the slowly varying oscillations;
extrapolating each of the corresponding models for each of the plurality of components in order to obtain a component prediction;
combining the component predictions of each of the plurality of components with the slowly varying oscillation component to generate a final prediction on the time series, representing predicted behavior of the online marketplace; and
presenting the final prediction.
1 Assignment
0 Petitions
Accused Products
Abstract
A data prediction method to apply to a time series. In some embodiments, the data may be decomposed into a superposition of two or more components, which each represent different facets of the data. In further embodiments presented herein, the data may be decomposed into components representing: slowly-varying oscillations; cyclical and known instantaneous (non-stationary) disturbances; and background stationary noise effects. Each component may then be subjected to its own prediction algorithm. The predicted values of each component may then be composed to obtain a final prediction of the original data.
-
Citations
20 Claims
-
1. A computer-implemented method comprising:
-
obtaining a time series, comprising real-world data over a specified period of time; decomposing the time series into a superposition of a plurality of components; for each one of the plurality of components, selecting a corresponding prediction algorithm; generating a corresponding model for each of the plurality of components and the slowly varying oscillations; extrapolating each of the corresponding models for each of the plurality of components in order to obtain a component prediction; combining the component predictions of each of the plurality of components with the slowly varying oscillation component to generate a final prediction on the time series, representing predicted behavior of the online marketplace; and presenting the final prediction. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
-
-
13. A system for making a prediction based on a time series, comprising:
-
a machine having a memory and at least one processor; and at least one module, executable by the at least one processor, comprising; a source module, configured to obtain the time series; a decomposition module, configured to decompose the time series into a superposition of a plurality of components; an algorithm selection module, configured to select an appropriate prediction algorithm to apply to each of the plurality of components; a modeling module, configured to model each of the components separately; a prediction module, configured to extrapolate each model in order to obtain a component prediction; a model summation module, configured to obtain a final prediction for the time series; and a presentation module, configured to present the final prediction. - View Dependent Claims (14, 15, 16, 17)
-
-
18. A non-transitory machine-readable storage medium storing a set of instruction that, when executed by at least one processor, causes the at least one processor to perform a set of operations comprising:
-
obtaining a time series; decomposing the residual into a superposition of a plurality of components; selecting a corresponding prediction algorithm to apply to each of the plurality of components based on one or more parameters of the corresponding component; generating a corresponding model for each of the plurality of components and the slowly varying oscillation component, based on the corresponding prediction algorithm; extrapolating each of the corresponding models for each of the plurality of components in order to obtain a component prediction; combining the component predictions for each of the plurality of components and the slowly varying oscillation component to create a final prediction for the time series; and presenting the final prediction. - View Dependent Claims (19, 20)
-
Specification