PATENT CLAIM ANALYSIS

Application Number: 16388119
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-08
Patent Classification: ["700", "110000"]

Abstract:
Machines can be controlled using advanced control systems that implement an automated version of singular spectrum analysis (SSA). For example, a control system can perform SSA on a time series having one or more time-dependent variables by: generating a trajectory matrix from the time series, performing singular value decomposition on the trajectory matrix to determine elementary matrices; and categorizing the elementary matrices into groups. The elementary matrices can be automatically categorized into the groups by: generating one or more w-correlation matrices based on spectral components associated with the time series, determining w-correlation values based on the one or more w-correlation matrices; categorizing the w-correlation values into a predefined number of w-correlation sets, and forming the groups based on the predefined number of w-correlation sets. The control system can then generate a predictive forecast using the groups and control operation of a machine using the predictive forecast.

Claim (Index 11):
A system comprising:\n a processing device; and a memory device including instructions that are executable by the processing device for causing the processing device to perform operations comprising: receiving a time series having one or more time-dependent variables; performing singular spectrum analysis on the time series at least partially by:\n generating a trajectory matrix from the time series, the trajectory matrix being a multi-dimensional representation of the time series, wherein the multi-dimensional representation of the time series has at least one dimension that is dependent on how many time-dependent variables are present in the time series; \n performing singular value decomposition on the trajectory matrix to generate elementary matrices; \n generating spectral components associated with the time series by performing diagonal averaging on the elementary matrices; and \n automatically categorizing the elementary matrices into a plurality of groups by:\n generating one or more w-correlation matrices based on the spectral components, each w-correlation matrix being generated by determining weighted correlations between a respective pair of the spectral components associated with a respective time-dependent variable present in the time series; \n determining w-correlation values based on the one or more w-correlation matrices; \n categorizing the w-correlation values into a predefined number of w-correlation sets such that, for each w-correlation set in the predefined number of w-correlation sets, all of the w-correlation values in the w-correlation set are above a predefined threshold value; and \n forming the plurality of groups based on the predefined number of w-correlation sets, each respective group in the plurality of groups including a respective subset of the elementary matrices corresponding to the w-correlation values in a respective w-correlation set among the predefined number of w-correlation sets; and \n \n determining a plurality of component time-series based on the plurality of groups; and \n generating a predictive forecast using the plurality of component time-series.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 100.0
- Lexical Diversity: 2.10526
- Patent Class: 700.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15883285', '15997371', '16233302', '16379470', '15788238']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3922398384521321
- 35 USC 102 Novelty (BERT): 0.5637048472625443
- Combined Prediction Score: 0.4093863393331733
- Mean Citation Score: 232.417014
- Max Citation Score: 458.8697
- Similarity Product: 403.4579517397464

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test