Mapping of Soil Contamination by Using Artificial Neural Networks and Multivariate Geostatistics
نویسندگان
چکیده
The work deals with the development and use of mixed models (artificial neural networks-ANN and modern geostatistical models) for the analysis of spatially distributed environmental data. When multivariate data have complex non-linear trends or high variability at different scales in the region of study it is proposed to use ANN to model non-linear large scale structures (deterministic trends) and then to apply multivariate geostatistics (co-kriging models) to the residuals. The proposed model is used for the spatial prediction of soil contamination by Chernobyl radionuclides.
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تاریخ انتشار 1997