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Rajasundrapandiyanleebanon et al., 2023 - Google Patents

Solar energy forecasting using machine learning and deep learning techniques

Rajasundrapandiyanleebanon et al., 2023

Document ID
15103556195287336667
Author
Rajasundrapandiyanleebanon T
Kumaresan K
Murugan S
Subathra M
Sivakumar M
Publication year
Publication venue
Archives of Computational Methods in Engineering

External Links

Snippet

Renewable energy sources are present copiously in the nature and are good for environmental conservation as they restore themselves and thus have considerable potential in the near future. It is hence important to concentrate on the forecast of these …
Continue reading at link.springer.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • 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

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