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Bi-LSTM deep neural network reservoir classification model based on the innovative input of logging curve response sequences
2021
IEEE Access
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For the first time, this study reveals the advantages of recurrent neural networks in the identification of heterogeneous reservoirs and proposes an optimal parameter bidirectional long short-term memory ...
(Bi-LSTM) recurrent neural network reservoir classification model with optimal parameters that can make full use of logging sequence information. ...
ACKNOWLEDGMENT Many thanks to the editor of IEEE-Access and anonymous reviewers. Their suggestions have improved the quality of the manuscript. ...
doi:10.1109/access.2021.3053289
fatcat:tctg4pwh3nftzjivblc4ri4d5y
Prediction Method of TBM Tunneling Parameters Based on Bi-GRU-ATT Model
2022
Advances in Civil Engineering
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This paper proposes an intelligent prediction method of TBM tunneling parameters based on bidirectional gate recurrent unit incorporating attention mechanism (Bi-GRU-ATT) and selects a complete tunneling ...
The results show that the prediction method of TBM tunneling parameters based on Bi-GRU-ATT model proposed in this paper has stronger learning and prediction capabilities. ...
Recurrent Neural Network 2.1. Bidirectional Gate Recurrent Unit. ...
doi:10.1155/2022/3743472
fatcat:ajczx2o42recpmtv6ghdrgc77i
The makers of the Protoaurignacian and implications for Neandertal extinction
2015
Science
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Acknowledgements: We thank the Wenner-Gren foundation, the British Association for Biological Anthropology and Osteoarchaeology and the Ruggles-Gates foundation for their financial support. ...
We also wish to thank Durham University for use of their facilities and equipment as well as the American Museum of Natural History, e Powell-Cotton Museum and the University of Zurich for granting access ...
e majority of these sites (n=46) also feature elongated material produced from a Levallois recurrent unidirectional/bidirectional strategy. ...
doi:10.1126/science.aaa2773
pmid:25908660
fatcat:6m44miosqzbxljew7jbfm5cm5q