Large-scale multi-detector predictive modeling
First Claim
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1. A system for predictive modeling, the system comprising:
- a computer processing device communicatively coupled to data sources operating in a railroad environment; and
logic executable by the computer processing device, the logic configured to implement a method, the method including;
generating a factor matrix for each univariate time series data in a set of sparse time series data collected from the data sources, the time series data including at least one of temperature, optical geometry, load, and acoustic data;
identifying a subset of the time series data as a feature selection based on application of a loss function;
generating a predictive model from the subset of the time series data; and
generating, from the predictive model, a prediction indicating an amount of time before a failure occurs with respect to a component of the railroad environment.
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Abstract
Predicting operational changes in a multi-detector environment includes generating, via a computer processing device, a factor matrix for each univariate time series data in a set of sparse time series data collected from data sources, identifying a subset of the time series data as a feature selection based on application of a loss function, and generating a predictive model from the subset of the time series data.
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Citations
7 Claims
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1. A system for predictive modeling, the system comprising:
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a computer processing device communicatively coupled to data sources operating in a railroad environment; and logic executable by the computer processing device, the logic configured to implement a method, the method including; generating a factor matrix for each univariate time series data in a set of sparse time series data collected from the data sources, the time series data including at least one of temperature, optical geometry, load, and acoustic data; identifying a subset of the time series data as a feature selection based on application of a loss function; generating a predictive model from the subset of the time series data; and generating, from the predictive model, a prediction indicating an amount of time before a failure occurs with respect to a component of the railroad environment. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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Specification