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
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;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
DOI :
10.1109/RSETE.2011.5966289
