Improving 3-PG calibration and parameterization using artificial neural networks
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DOI: 10.1016/j.ecolmodel.2023.110301
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- Piñeiro, Gervasio & Perelman, Susana & Guerschman, Juan P. & Paruelo, José M., 2008. "How to evaluate models: Observed vs. predicted or predicted vs. observed?," Ecological Modelling, Elsevier, vol. 216(3), pages 316-322.
- Wen, Xuding & Zhao, Zhonghui & Deng, Xiangwen & Xiang, Wenhua & Tian, Dalun & Yan, Wende & Zhou, Xiaolu & Peng, Changhui, 2014. "Applying an artificial neural network to simulate and predict Chinese fir (Cunninghamia lanceolata) plantation carbon flux in subtropical China," Ecological Modelling, Elsevier, vol. 294(C), pages 19-26.
- Song, Xiaodong & Bryan, Brett A. & Paul, Keryn I. & Zhao, Gang, 2012. "Variance-based sensitivity analysis of a forest growth model," Ecological Modelling, Elsevier, vol. 247(C), pages 135-143.
- Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
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Keywords
Process-based model; Eucalypt; Forest management; Machine learning;All these keywords.
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