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Meng et al., 2022 - Google Patents

A novel few-shot learning approach for wind power prediction applying secondary evolutionary generative adversarial network

Meng et al., 2022

Document ID
13194376534181333474
Author
Meng A
Chen S
Ou Z
Xiao J
Zhang J
Chen S
Zhang Z
Liang R
Zhang Z
Xian Z
Wang C
Yin H
Yan B
Publication year
Publication venue
Energy

External Links

Snippet

The accuracy and stability of wind power forecasting are very important for the operation of wind farms. However, for the newly built wind farms without sufficient historical data, it is difficult to make a more accurate prediction. Therefore, it is of great significance to explore a …
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Classifications

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    • G06N3/08—Learning methods
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    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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    • G06K9/62—Methods or arrangements for recognition using electronic means
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
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    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
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    • G06K9/6267—Classification techniques
    • G06K9/6279—Classification techniques relating to the number of classes
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