Acid Sulfate Soils Classification and Prediction from Environmental Covariates Using Extreme Learning Machines

Author:

Atsemegiorgis Tamirat,Espinosa-Leal Leonardo,Lendasse Amaury,Mattbäck Stefan,Björk Kaj-Mikael,Akusok Anton

Publisher

Springer Nature Switzerland

Reference18 articles.

1. Akusok, A., Björk, K.M., Miche, Y., Lendasse, A.: High-performance extreme learning machines: a complete toolbox for big data applications. IEEE Access 3, 1011–1025 (2015)

2. Proceedings in Adaptation, Learning and Optimization;A Akusok,2021

3. Proceedings in Adaptation, Learning and Optimization;A Akusok,2021

4. Andriesse, W., van Mensvoort, M.: Acid sulfate soils, distribution and extent, p. 6. Marcel Dekker (2002)

5. Auri, J., et al.: From a general survey to risk management - acid sulfate soils are Finland’s most persistent environmental problem, but research can mitigate the harms they cause (2022). https://www.gtk.fi/en/current/from-a-general-survey-to-risk-management-acid-sulfate-soils-are-finlands-most-persistent-environmental-problem-but-research-can-mitigate-the-harms-they-cause

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