Recognition of dominant driving factors behind sap flow of Liquidambar formosana based on back-propagation neutral network method

Jie Tu, Qijing Liu & Jianping Wu
Aims: This study focused on the applicability of back-propagation (BP) neural networks in simulating sap flow (SF) using meteorological factors and a phenological index (PI) for Liquidambar formosana, a deciduous broad-leaf tree species in subtropical China, and thus providing a useful and promising alternative to traditional methods for transpiration prediction. Methods: Three-layered BP models with an architecture 4-10-1 (four neurons in the input layer, ten neurons in the hidden layer and one neuron in the...
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