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2013 (Vol. 5, Issue: 16)
Article Information:

Leaf Mass Estimation Affected by Leaf Shape and Tree Height based on Simulation and Four-Layer Hidden-node Neural Network

Zi-Yue Chen, Yuan-Biao Zhang, Zhao-Wei Wang and Qiu-Ye Qian
Corresponding Author:  Zi-Yue Chen 

Key words:  Four -layer hidden-node neural network model, leaf mass, shape, simulation, , , ,
Vol. 5 , (16): 4142-4148
Submitted Accepted Published
July 31, 2012 September 08, 2012 April 30, 2013
Abstract:

Leaf mass, a vital parameter of forest ecology and physiology, is estimated in this study. According to the simulation result in this study, leaf shape makes little contribution to the exposure area. Moreover, a four-layer hidden-node neural network model is used in the new model, analyzing correlation between leaf mass and height of trees. Leaves of various areas are tested as sensitivity analysis for the simulation which studied the influence of leaf shape on exposure area. Finally, leaf mass is estimated by a statistical model based on the regression relationship of sapwood area and leaf mass.
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  Cite this Reference:
Zi-Yue Chen, Yuan-Biao Zhang, Zhao-Wei Wang and Qiu-Ye Qian, 2013. Leaf Mass Estimation Affected by Leaf Shape and Tree Height based on Simulation and Four-Layer Hidden-node Neural Network.  Research Journal of Applied Sciences, Engineering and Technology, 5(16): 4142-4148.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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