Predicting IGS RTS Corrections Using ARMA Neural Networks
An autoregressive moving average neural network (ARMANN) model is applied to predict IGS real time service corrections. ARMA coefficients are determined by applying a neural network to IGS02 orbit/clock corrections. Other than the ARMANN, the polynomial and ARMA models are tested for comparison. An...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi Limited
2015-01-01
|
| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2015/851761 |