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A Methodology for Automatic Analysis and Modeling of Spatial Environmental Data

Authors:
Mikhail Kanevski

Keywords: environmental geospatial data; automatic data modelling; machine learning algorithms

Abstract:
The research paper deals with a step-by-step methodology for the automatic modeling of geospatial environmental data. The methodology proposed is based on general regression neural networks (GRNN) and probabilistic neural networks (PNN) as modeling tools. GRNN and PNN are nonparametric nonlinear models suitable for the automatic analysis, modeling, and spatial predictions of complex environmental data. The simulated and real data case studies illustrating the methodology are considered and discussed.

Pages: 105 to 107

Copyright: Copyright (c) IARIA, 2013

Publication date: February 24, 2013

Published in: conference

ISSN: 2308-393X

ISBN: 978-1-61208-251-6

Location: Nice, France

Dates: from February 24, 2013 to March 1, 2013