Ensemble Encoder-Decoder Models for Predicting Land Transformation

Land development is a dynamic and complex processinfluenced by a system of interconnected driving variables. Predicting such a process is important in mitigating severe climate situations and improving the resiliency of communities. Current predictive models in land transformation have not paid a se...

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Vydáno v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 14; s. 11429 - 11438
Hlavní autoři:	Pourmohammadi, Pariya, Strager, Michael P., Adjeroh, Donald A.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Artificial neural networks Biological system modeling Climate models Coders Computational modeling Convolutional neural networks Convolutional neural networks (CNNs) Cubes Data models developed land expansion evidence fusion Genetic transformation Land development land transformation prediction Neural networks Performance prediction Prediction models Predictive models Scientific visualization Solid modeling Stability Three-dimensional displays Transformations Two dimensional models Watersheds
ISSN:	1939-1404, 2151-1535
On-line přístup:	Získat plný text
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