SUPERVISED NEURAL NETWORK TO PREDICT UNLABELED RAIN RATES

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United States of America Patent

APP PUB NO 20170357029A1
SERIAL NO

15182138

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ATTORNEY / AGENT: (SPONSORED)

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Abstract

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In an embodiment, radar observation data for time points are received at an input layer of a rain rate prediction neural network. The radar observations are forward propagated via hidden layers of the network to determine rain rates for the time points. The rain rates are integrated over a time period, determined based on the time points, to determine a predicted rainfall amount. The predicted rainfall amount is compared with an actual rainfall amount, determined based on received rainfall measurements, to determine an error. If the error does not satisfy certain criteria, then the error is apportioned to each of the time points, the apportioned errors are back propagated via the hidden layers, and weights associated with nodes in the hidden layers are updated. The radar observation data is again forward propagated via the layers, multiplied by the updated weights, and used to determine new rain rates.

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Patent Owner(s)

Patent OwnerAddress
THE CLIMATE CORPORATION201 THIRD STREET SUITE 1100 ATTN LEGAL SAN FRANCISCO CA 94103

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
LAKSHMANAN, VALLIAPPA Bellevue, US 7 21

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