DocumentCode
2481339
Title
The application of RBF neural network in turfgrass quality evaluation
Author
Xiao, Bo ; Fei, Yongjun ; Liu, Lecheng ; Rao, Guizhen ; Han, Liebao
Author_Institution
Coll. of Horticulture & Garden, Yangtze Univ., Jingzhou, China
fYear
2011
fDate
24-26 June 2011
Firstpage
7935
Lastpage
7938
Abstract
A model for the comprehensive turfgrass quality evaluation has been constructed based on the RBF neural network. The structure of the neural network model is described. And then the model is trained with samples and tested in MATLAB. Practice shows that the result has better precision and reliability comparing with other methods. With its fast convergence speed and good classification capability, the RBF-ANN is convenient in evaluating turfgrass quality. It has a wide applications prospect with extensive ability.
Keywords
forestry; quality management; radial basis function networks; RBF neural network; radial basis function network; turfgrass quality evaluation; Artificial neural networks; Atmospheric modeling; Forestry; MATLAB; Mathematical model; Presses; Radial basis function networks; RBF neural network; Turfgrass quality evaluation; model;
fLanguage
English
Publisher
ieee
Conference_Titel
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9172-8
Type
conf
DOI
10.1109/RSETE.2011.5966289
Filename
5966289
Link To Document