Title :
Assessing the Intensity of Urban Land Use Based on Radial Basis Function Network
Author :
Xu, Weisheng ; Chang, Sheng ; Li, Jiangfeng
Author_Institution :
Fac. of Resources, China Univ. of Geosci., Wuhan, China
Abstract :
Urban land intensive use is very important to China.Traditional intensity evalua- tion methods of land use is highly influenced by man´s subjective impact,thus the evaluation result is not accurate enough. In this paper, Radial Basis Function Network (RBFN) was set up to assess the urban land intensive use.Ezhou Municipal in Hubei province was taken as a case study. The results show that urban land use of Ezhou Municipal is on medium intensive level, which is consistent with the actual land use situation. Taking RBFN to assess the urban land intensive use is feasible, which can simplify the evaluation process, avoid man´s subjective impact,and get relatively more accurate results.Compared with Back Propagation artificial neural networks (BPNN),RBFN is more convenient and effective.
Keywords :
land use planning; radial basis function networks; Ezhou Municipal; back propagation artificial neural network; intensity evaluation method; radial basis function network; urban land intensive use; Artificial neural networks; Cities and towns; Euclidean distance; Geology; Radial basis function networks; Training; Transfer functions;
Conference_Titel :
Database Technology and Applications (DBTA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6975-8
Electronic_ISBN :
978-1-4244-6977-2
DOI :
10.1109/DBTA.2010.5659097