Solution to the model of nonlinear multiregression based on generalized Choquet integral and its application in estimating forest volume

Author

Xiao, Tao ; Zhang, Ning ; Huang, Dong-mei

Author_Institution

Coll. of Sci., Agric. Univ. of Hebei, Baoding, China

Volume

12

fYear

2010

fDate

22-24 Oct. 2010

Abstract

Multiregression is one of the most common approaches used in data mining. The crux of using a nonlinear multiregression model is how to effectively determine the unknown parameters. In this paper, PSO(Particle Swarm Optimization) is used to solve nonlinear multiregression based on generalized Choquet integrals. And we apply the model to estimate the forest stock volume of Saihanba forest farm. Experimental results show that PSO is an effective algorithm for solving nonlinear multiregression in terms of global-searching ability and convergence speed. The application of this model in estimation of the forest volume provides scientific basis for dynamic and scientific management of forest resource.

Keywords

data mining; forestry; particle swarm optimisation; regression analysis; Saihanba forest farm; data mining; forest resource scientific management; forest stock volume estimation; generalized Choquet integral; global searching ability; nonlinear multiregression model; particle swarm optimization; Computational modeling; Conferences; Estimation; Mathematical model; Particle swarm optimization; Prediction algorithms; Solid modeling; Choquet integrals; Forest stock volume; Nonlinear multiregression; PSO;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Application and System Modeling (ICCASM), 2010 International Conference on

Conference_Location

Taiyuan

Print_ISBN

978-1-4244-7235-2

Electronic_ISBN

978-1-4244-7237-6

Type

conf

DOI

10.1109/ICCASM.2010.5622121

Filename

5622121