A Comparative Study of Prediction in Seabed Mapping

Ghedhban Swadi*, Karim Al-jebory**, Dave Holifield***
*-** Department of Engineering, University of Wales Institute, Cardiff, UK.
*** Faculty of Engineering, Al Isra University, Amman, Jordan.
Periodicity:January - March'2013
DOI : https://doi.org/10.26634/jse.7.3.2169

Abstract

In this paper, the performance of two dynamic neural network based predictors in seabed mapping is investigated. The two types of predictors are; the Focused Time- Delay Neural Network (FTDNN) based predictor and the Nonlinear Auto regressive Network with Exogenous Inputs (NARX) predictor. A testing platform has been developed that consists of seabed simulator and sonar simulator. Results show the NARX predictor outperforms the FTDNN predictor.

Keywords

Simulation, Neural Network, Predictor, Sonar, Seabed.

How to Cite this Article?

Swadi, G., Aljebory, K. M., and Holifield, D. (2013). A Comparative Study of Prediction in Seabed Mapping. i-manager’s Journal on Software Engineering, 7(3), 9-14. https://doi.org/10.26634/jse.7.3.2169

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