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›› 2006, Vol. 42 ›› Issue (zk): 24-30.

• 论文及研究报告 • Previous Articles     Next Articles

Application of Fuzzy Distribution Functions to Stand Diameter Distribution of Cunninghamia lanceolata Plantations

Duan Aiguo,Zhang Jianguo   

  1. Research Institute of Forestry,CAF Key Laboratory of Tree Breeding and Cultivation,State Forestry Administration Beijing 100091
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-09-25 Published:2006-09-25

Abstract: According to the correspondence of mathematical characteristics of Fuzzy functions and distribution interval of stand diameter cumulative percentage series,this paper introduced Fuzzy distribution functions to model diameter distribution of Chinese Fir (Cunninghamia lancelata) plantation,and discussed their adaptability and reasons for discrepancy of simulation precision of Fuzzy distributions. Among Fuzzy distribution functions,except that Fuzzy-Γ1 had relatively low precision,Fuzzy functions,like Fuzzy-Γ2,Fuzzy-Γ3,Fuzzy-Γ4 and Fuzzy-C,all presented good simulation properties,and the parameters of Fuzzy-Γ3 had close correlation with stand age and density. The generalized Fuzzy-Γ5 distribution had the best simulation properties,and the highest precision,the value of its parameter c was mostly distributed nearby 3 and 4,indicating that stand diameter distribution was mainly similar to the forms of Fuzzy-Γ3 and Fuzzy-Γ4. Through analysis of relationship between parameters of Fuzzy-Γ5 distribution and stand factors,the effects of stand factors such as age and density on distribution parameters were discussed. After analyzing the mathematical quality and simulation properties of nine kinds of distribution functions such as Fuzzy-Γ-5 and Logistic etc.,it was concluded that inflection point of stand diameter cumulative distribution curve have a main flexible interval (0.4~0.6) and a central distribution point (0.5 or so),for average simulation precision,when the inflection point of distribution function lies in the main interval,its precision is relatively high,and the closer to the central point,the higher the precision is.

Key words: Fuzzy distribution function, diameter distribution models, inflection point, stand factors