TY  - JOUR
AU  - Salcedo Sanz, S.
AU  - Portilla Figueras, J.A.
AU  - Ortiz Garcíaq, E.G.
AU  - Pérez Bellido, A.M.
AU  - García Herrera, Ricardo
AU  - Elorrieta, J.I.
PY  - 2009
DO  - 10.1016/j.chemolab.2009.07.012
SN  - 0169-7439
UR  - https://hdl.handle.net/20.500.14352/43028
T2  - Chemometrics and intelligent laboratory sistems
AB  - This paper discusses the performance of Radial Basis Function networks (RBF) in a problem of spatial regression of pollutants in Madrid. Specifically, the spatial regression of NO_(x) and O_(3) is considered, in such a way that, starting from a set of...
LA  - eng
M2  - 79
PB  - Elsevier Science BV
KW  - Land-use regression
KW  - Pollution monitoring network
KW  - Fine particulate matter
KW  - RBF neural-networks
KW  - Ozone concentration
KW  - Prediction
KW  - Optimization
KW  - Algorithm
KW  - Emissions
KW  - Episodes
TI  - Spatial regression analysis of NO_(x) and O_(3) concentrations in Madrid urban area using Radial Basis Function networks
TY  - journal article
VL  - 99
ER  -