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. 2018 May 21;8:7911. doi: 10.1038/s41598-018-26350-3

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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The above figure shows the basis upon which the final network architecture was chosen. (a) Shows that using the GDL is superior to the WCE; (b) shows that having a convolutional layer as the first layer is superior to an MDLSTM layer; (c) and (d) show that using 32 units and 2 layers, respectively, produces, on average, the strongest network.