*This record, in combination with the inverse_target_data record
with the same index, allows you to specify target data (e.g. experimental data
to determine model parameters or required data for optimization)
to be used in the inverse modeling.
Parameters will be determined by least squares minimization, i.e. the sum
*

*is minimized ( and are the penalty factor and
target value, see inverse_target_data).
In the example below, the temperature (2.33) at node
3 and the temperature (80.2) at post point 10 were measured and are used for
inverse modeling of the conductivity.
Both experimental results are imposed with a penalty factor 100 in the
inverse modeling. In total 20 iterations are used to estimate the conductivity.
The initial estimate for the conductivity needs to be specified via
the group_condif_conductivity record; while iterating this record will be updated
with new estimates.
*

...

condif_temperature

end_initia

...

inverse_target 1 -node_dof 3 -temp

inverse_target_data 1 2.33 100.

inverse_target 2 -post_point_dof 10 -temp

inverse_target_data 2 80.2 100.

inverse_parameter 0 -group_condif_conductivity 0 0

inverse_iterations 0 20

...

end_data