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Reconstructing input for artificial neural networks based on embedding theory and mutual information to simulate soil pore water salinity in tidal floodplain

التفاصيل البيبلوغرافية
العنوان: Reconstructing input for artificial neural networks based on embedding theory and mutual information to simulate soil pore water salinity in tidal floodplain
المؤلفون: Fawen Zheng, Keunyea Song, Detong Sun, Yongshan Wan, Marion Hedgepeth
المصدر: Water Resources Research. 52:511-532
بيانات النشر: American Geophysical Union (AGU), 2016.
سنة النشر: 2016
مصطلحات موضوعية: Hydrology, geography, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Artificial neural network, Floodplain, Computer science, 0208 environmental biotechnology, 02 engineering and technology, Mutual information, 01 natural sciences, 020801 environmental engineering, Salinity, Pore water pressure, Embedding theory, Embedding, 0105 earth and related environmental sciences, Water Science and Technology
تدمد: 1944-7973
0043-1397
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::b0aefa98b0fd050feefb2dbe35faff47
https://doi.org/10.1002/2014wr016875
حقوق: OPEN
رقم الأكسشن: edsair.doi...........b0aefa98b0fd050feefb2dbe35faff47
قاعدة البيانات: OpenAIRE
الوصف
تدمد:19447973
00431397