Abstract
Generally, backcalculation analysis is greatly affected by errors in the measured deflection data. Average of several data set is normally used in static backcalculation in order to reduce effect of these errors. However, this procedure can not be employed in case of time series data. A rather time consuming procedure is used, where backcalculation is performed for each data set and then an average of the backcalculated layer properties is determined. This paper proposes a new method where several sets of time series data can be used in dynamic backcalculation to determine an average result. Computation time is similar to the case of one data set. Analysis domain and the number of nodes were also examined.
