FORECASTING LAND-BASED ENVIRONMENTAL VARIABLES USING SIMILARITY ANALYSIS AND TEMPORAL GRAPH CONVOLUATIONAL NEURAL NETWORKS
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United States of America Patent
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Issued Date -
Apr 4, 2024
app pub date -
Oct 4, 2022
filing date -
Oct 4, 2022
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Abstract
Embodiments are directed to a computer-implemented method of analyzing a land region that has been decomposed into a plurality of regular or irregular sub-regions. The computer-implemented method includes applying, using a processor system, a feature extraction process that extracts a set of sub-region environmental descriptors for each of the plurality of sub-regions. The processor system applies a similarity analysis to the set of sub-region environmental descriptors to generate groups of the plurality of sub-regions. The processor system creates a plurality of group-based graphs by encoding each of the groups into a corresponding group-based graph. A spatio-temporal neural network is used to train a model based at least in part on the plurality of group-based graphs.
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