Abstract:

Objective: Aiming at the complex relationships between neighborhood trees characteristics and subject tree crown width,a method of estimating crown width based on adaptive neuro-fuzzy inference system was proposed to improve the intelligent level of estimating crown width. Method: Chinese fir was taken as the research object. According to the distance and azimuth of the neighborhood trees relative to the subject tree,a method of adding trees in quadrants was presented to build spatial structural units. One hundred sets of data which contained crown width in four aspects,distances and azimuths were measured,computing method of two independent variables,including neighborhood crown width and distance from the subject tree,were proposed,and then the ratio of the subject tree crown width to the neighborhood crown width was defined as the dependent variable. According to the sample data,the nonlinear mapping relations among variables were analyzed,and twenty-five fuzzy logic inference rules were established. Azero-order Takagi-Sugeno model,which was composed of two inputs and one output,was designed. The adaptive neuro-fuzzy inference system was trained by seventy sets of data,and tested by thirty sets of data. It was contrasted with multi-element linear regression and back propagation neural network. Result: The linear relationships of crown width estimated by three method and the true value all reached significant levels. On inspection,determination coefficients of this method,back propagation neural network and multi-element linear regression were 0.71,0.67,and 0.66,respectively. Conclusion: According to the neighborhood trees characteristics in the spatial structural unit,this method could directly,effectively and intelligently estimate the subject tree crown width without the independent variables those contain attributes of the subject tree.

Key words: adaptive neuro-fuzzy inference system, crown width, estimation, spatial structural unit, intelligentialize