Weekly reconstruction of pH and total alkalinity in an upwelling-dominated coastal ecosystem: The case of Ría de Vigo (NW Spain) between 1992 and 2019 (Discussions version)
The item is made of 6 files: 1) README.txt; 2) INTECMAR_NN-database.csv: Dataset containing all the input variables used compute the time series of AT and pH as well as these two computed variables; 3) Training_database.xlsx: Dataset containing the data to train and test the neural networks; 4) pH_N...
| Authors: | , , |
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| Format: | conjunto de datos |
| Publication Date: | 2020 |
| Country: | España |
| Institution: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repository: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/220930 |
| Online Access: | http://hdl.handle.net/10261/220930 |
| Access Level: | Open access |
| Keyword: | Total alkalinity pH Time series Neural networks Ocean acidification Seasonal cycles Long-term trends http://aims.fao.org/aos/agrovoc/c_8721 http://aims.fao.org/aos/agrovoc/c_37467 http://aims.fao.org/aos/agrovoc/c_51289d95 alkalinity neural networks ocean acidification |
| Summary: | The item is made of 6 files: 1) README.txt; 2) INTECMAR_NN-database.csv: Dataset containing all the input variables used compute the time series of AT and pH as well as these two computed variables; 3) Training_database.xlsx: Dataset containing the data to train and test the neural networks; 4) pH_NN.mat is the neural network object used to compute the pH time series; 5) AT_NN.mat is the neural network object used to compute the total alkalinity time series; 6) Source_code.rar contains the MATLAB files to configure, train and validate the neural networks created in this study |
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