Data fusion in radial basis function networks for spatial regression

被引：12

作者：

Hu, TM ^{[1
]}

Sung, SY ^{[1
]}

机构：

[1] Natl Univ Singapore, Dept Comp Sci, Singapore 117543, Singapore

来源：

NEURAL PROCESSING LETTERS | 2005年 / 21卷 / 02期

关键词：

data fusion; spatial autocorrelation; spatial regression; radial basis function network;

D O I：

10.1007/s11063-004-7776-5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Conventional radial basis function (RBF) networks for spatial regression assume independent and identical distribution and ignore spatial information. In contrast to input fusion, we push spatial information further into RBF networks by fusing output from hidden and output layers. Three case studies demonstrate the advantage of hidden fusion over others and indicate the optimal value is around 1 for the coefficient used in hidden fusion, which links the output from the hidden layer for each site with their neighbors.

引用

页码：81 / 93

页数：13

共 27 条

[11] HEDONIC HOUSING PRICES AND DEMAND FOR CLEAN-AIR [J].

HARRISON, D ;

RUBINFELD, DL .

JOURNAL OF ENVIRONMENTAL ECONOMICS AND MANAGEMENT, 1978, 5 (01) :81-102

[12] Layered Neural Networks with Gaussian Hidden Units as Universal Approximations [J].

Hartman, Eric J. ;

Keeler, James D. ;

Kowalski, Jacek M. .

NEURAL COMPUTATION, 1990, 2 (02) :210-215

[13]

Hermes L, 2001, PROC CVPR IEEE, P442

[14] UNSUPERVISED TEXTURE SEGMENTATION USING GABOR FILTERS [J].

JAIN, AK ;

FARROKHNIA, F .

PATTERN RECOGNITION, 1991, 24 (12) :1167-1186

[15] Bayesian contextual classification based on modified M-estimates and Markov random fields [J].

Jhung, YH ;

Swain, PH .

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1996, 34 (01) :67-75

[16]

Kaufman L., 1990, Finding Groups in Data: An Introduction to Cluster Analysis, DOI DOI 10.1002/9780470316801

[17]

Legendre P., 1987, NATO ASI Series Series G Ecological Sciences, V14, P289

[18]

LESAGE JP, 1999, MATLAB TOOLBOX SPATI

[19] Signal detection using the radial basis function coupled map lattice [J].

Leung, H ;

Hennessey, G ;

Drosopoulos, A .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2000, 11 (05) :1133-1151

[20] A GEOSTATISTICAL BASIS FOR SPATIAL WEIGHTING IN MULTIVARIATE CLASSIFICATION [J].

OLIVER, MA ;

WEBSTER, R .

MATHEMATICAL GEOLOGY, 1989, 21 (01) :15-35

← 1 2 3 →