Machine Learning for Spatial Environmental Data: Theory,...

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Machine Learning for Spatial...

Machine Learning for Spatial Environmental Data: Theory, Applications, and Software (Environmental Sciences: Environmental Engineering)

Mikhail Kanevski, Vadim Timonin, Alexi Pozdnukhov

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This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and mapping of spatially distributed data. It presents basic geostatistical algorithms as well. The authors describe new trends in machine learning and their application to spatial data. The text also includes real case studies based on environmental and pollution data. It includes a CD-ROM with software that will allow both students and researchers to put the concepts to practice.

Kategori:

Science (General)

Tahun:

2009

Edisi:

Har/Cdr

Penerbit:

EFPL Press

Bahasa:

english

Halaman:

371