Identify data sources for neural network
First Claim
1. A system for identifying data sources for a neural network comprising:
- a module for determining load curves for each of selected data sets;
a module for determining a global difference measure and a global similarity measure for each load curve of each selected data sets;
a module for determining a set of data sets with lowest value global difference measure;
a module for determining a set of data sets with largest value global similarity measure;
a module for determining a union of the sets of lowest value difference measure and the sets of largest value similarity measure;
a module for determining for each set in the union one of a local similarity measure and a local difference measure; and
a module for selecting a set of reduced data sets based on one of the local similarity measure and the local difference measure.
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Accused Products
Abstract
A system, method, and device for identifying data sources for a neural network are disclosed. The exemplary system may have a module for determining load curves for each selected data set. The system may also have a module for determining a global difference measure and a global similarity measure for each load curve of each selected data set. The system may have a module for determining a set of data sets with lowest value global difference measure. The system may also have a module for determining a set of data sets with largest value global similarity measure. The system may also have a module for determining a union of the sets of lowest value difference measure and the sets of largest value similarity measure. The system may also have a module for determining for each set in the union one of a local similarity measure and a local difference measure and a module for selecting a set of reduced data sets based on one of the local similarity measure and the local difference measure.
11 Citations
20 Claims
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1. A system for identifying data sources for a neural network comprising:
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a module for determining load curves for each of selected data sets;
a module for determining a global difference measure and a global similarity measure for each load curve of each selected data sets;
a module for determining a set of data sets with lowest value global difference measure;
a module for determining a set of data sets with largest value global similarity measure;
a module for determining a union of the sets of lowest value difference measure and the sets of largest value similarity measure;
a module for determining for each set in the union one of a local similarity measure and a local difference measure; and
a module for selecting a set of reduced data sets based on one of the local similarity measure and the local difference measure. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for identifying data sources for a neural network comprising the following actions:
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determining load curves for each selected data sets;
determining a global difference measure and a global similarity measure for each load curve of each selected data sets;
determining a set of data sets with lowest value global difference measure;
determining a set of data sets with largest value global similarity measure;
determining a union of the sets of lowest value difference measure and the sets of largest value similarity measure;
determining for each set in the union one of a local similarity measure and a local difference measure; and
selecting a set of reduced data sets based on one of the local similarity measure and the local difference measure. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15)
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16. A system for identifying matching data sources for a neural network based very short term load prediction in operating a power generation unit comprising:
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a module for determining load curves for each of a selected date data sets;
a module for determining a global difference measure and a global similarity measure for each load curve of each selected date data sets;
a module for determining a set of date data sets with lowest value global difference measure;
a module for determining a set of date data sets with largest value global similarity measure;
a module for determining a union of the date sets of lowest value difference measure and the date sets of largest value similarity measure;
a module for determining for each date set in the union one of a local similarity measure and a local difference measure; and
a module for selecting a data set of reduced data sets based on one of the local similarity measure and the local difference measure. - View Dependent Claims (17, 18, 19, 20)
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Specification