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Spatial interpolation algorithms are vital to environmental monitoring systems, especially for the real-time monitoring systems of critical variables in converting the point measurements to spatial continuous surfaces. This paper describes the spatial interpolation of meteorological observations (air temperature as an example) using a feed-forward back-propagation neural network based on the environment-affecting...
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