Abstract
<p class="ABSTRACT">The transition from ellipsoidal geodetic coordinates to rectangular 3D coordinates is quite simple, while the reverse procedure is somehow more complex due to the mathematical relationship between the ellipsoidal width and 3D coordinates. Until now, several methods for solving this problem have been defined and described in geodetic literature. In this paper, the possibility of applying a backpropagation algorithm based on a multilayer perceptron (Multilayer Perceptron – MLP) neural network for the transformation of rectangular 3D geodetic into ellipsoidal coordinates is analyzed. The applied MLP model is based on Bayesian regularization (BR). The adequacy of the model was verified by a robustness test and a cross-validation test. Based on the obtained results, it was concluded that the MLP neural network can be used for the transformation from rectangular 3D to ellipsoidal coordinates. Future research should analyze the possibility of applying this procedure to solve the problem of data transformation.</p>
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
