Application of empirical mode decomposition, particle swarm optimization, and support vector machine methods to predict stream flows
Author:
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
Link
https://link.springer.com/content/pdf/10.1007/s10661-023-11700-0.pdf
Reference55 articles.
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2. Chen, W., Chen, X., Peng, J., Panahi, M., & Lee, S. (2021). Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and satin bowerbird optimizer. Geoscience Frontiers, 12(1), 93–107. https://doi.org/10.1016/j.gsf.2020.07.012
3. Chun-Lin, L. (2010). A tutorial of the wavelet transform. NTUEE, Taiwan, 21, 22.
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5. Dehghani, R., & Poudeh, H. T. (2021). Applying hybrid artificial algorithms to the estimation of river flow: A case study of Karkheh catchment area. Arabian Journal of Geosciences, 14(9), 1–19. https://doi.org/10.1007/s12517-021-07079-2
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