  A toy detector has been designed to simulate central detectors in reactor
neutrino experiments in the paper. The electron samples from the Monte-Carlo
simulation of the toy detector have been reconstructed by the method of
Bayesian neural networks (BNN) and the standard algorithm, a maximum likelihood
method (MLD), respectively. The result of the event reconstruction using BNN
has been compared with the one using MLD. Compared to MLD, the uncertainties of
the electron vertex are not improved, but the energy resolutions are
significantly improved using BNN. And the improvement is more obvious for the
high energy electrons than the low energy ones.

Data Analysis, Statistics and Probability;High Energy Physics - Experiment;Instrumentation and Detectors