Abstract:
Leveling procedure is required for the design of the engineering
projects and is usually carried out practically in the field, which can be
considered as one of the most costly procedures. However; some
mathematical models are used for condensing spot heights with a relatively
low cost.
Artificial neural networks appear as one of the prediction methods used in
many disciplines. Although it is widely applied in different fields, it is not
widely used in surveying.
The objective of this research is to test the possibility of using such a method
for height prediction, and assessing it’s precision in comparison with
currently used algorithms, taking into account two factors; number of
iterations and random seed number (a value that is used to stabilize the
weight selection).
It is found that artificial neural networks can give precisions in the range of
3%, 2.61%, and 6.37% of the height difference for flat, gently rolling and
mountainous areas respectively. However; for surveyors more improvements
are needed to make this method simpler
