2005Nanjing Linye Daxue xuebaoRequires access

Measured Criteria and Application of Nonlinear Model Linearized

She Guang-hui

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Abstract

In the forest research,many tree growth models are nonlinear ones.The classical method dealing with these nonlinear models is linear approximation using the approximate value of parameter,due to the difference of nonlinearity among different nonlinear models,in which the nonlinear models cannot be linearized.This paper introduces a method to measure nonlinearity of nonlinear models and presents the intrinsic nonlinearity and parameter-effects nonlinearity of nonlinear models.Forestry resources's surveying sample data is tested by use of this method.The result shows that this method has many useful characteristics for the tree growth models.

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What this paper is about

In the forest research,many tree growth models are nonlinear ones.The classical method dealing with these nonlinear models is linear approximation using the approximate value of parameter,due to the difference of nonlinearity among different nonlinear models,in which the nonlinear models cannot be linearized.This paper introduces a method to measure nonlinearity of nonlinear models and presents the intrinsic nonlinearity and parameter-effects nonlinearity of nonlinear models.Forestry resources's surveying sample data is tested by use of this method.The result shows that this method has many useful characteristics for the tree growth models.

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Available abstract

In the forest research,many tree growth models are nonlinear ones.The classical method dealing with these nonlinear models is linear approximation using the approximate value of parameter,due to the difference of nonlinearity among different nonlinear models,in which the nonlinear models cannot be linearized.This paper introduces a method to measure nonlinearity of nonlinear models and presents the intrinsic nonlinearity and parameter-effects nonlinearity of nonlinear models.Forestry resources's surveying sample data is tested by use of this method.The result shows that this method has many useful characteristics for the tree growth models.

Key concepts: Nonlinear system, Tree (set theory), Applied mathematics, Measure (data warehouse), Nonlinear model, Mathematics, Linear model, Value (mathematics)

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