  Further development of the method of computational experiments for solving
ill-posed problems is given. The effective (unoverstated) estimate for solution
error of the first-kind equation is obtained using the truncating singular
numbers spectrum of an operator. It is proposed to estimate the magnitude of
the truncation by results of solving model (training, learning) examples close
to the initial example (problem). This method takes into account an additional
information about the solution and gives a new principle for choosing the
regularization parameter and error estimate for equation solution by the
Tikhonov regularization method. The method is illustrated by a numerical
example from the inverse problem of spectroscopy.
