Soil Suitability Evaluation Based on PSO-SVM M odel
WANG Ya-yun
ZHAO Yan-ling
HE Ting-ting
XIA Qing
HOU Zhan-dong
SHI Juan-juan
LIU Ya-ping
Abstract：Soil suitability evaluation is an important means to obtain land quality status ,and can provide important basis for the land planning ,management and decision-making .In this paper ,the support vector machine (SVM ) theory is introduced to the field of soil suitability evaluation .Ai-ming at the randomness of artificial selection punishment coefficient (C) and kernel function pa-rameter(σ) ,a PSO-SVM model is constructed by using particle swarm optimization (PSO ) to achieve higher evaluation accuracy .The radial basis function (RBF) is used as the kernel function in SVM model .Based on the model construction ,Xiluodu Hydropower Station Gullah Resettlement Area was chosen as an example ;the PSO-SVM model was applied to evaluate soil suitability ,and was compared with BP neural network and normal SVM model .The results showed that PSO-SVM significantly improved the accuracy of soil classification ,compared with BP neural network and the SVM model .Therefore ,PSO-SVM is a high-precision soil suitability evaluation model .
Keywords：support vector machineparticle swarmcomprehensive evaluationsoil suitability
Publication Date：2013-01-01
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：5( 49-53 )