  Multi-gap Resistive Plate Chamber(MRPC) is a widely used timing detector with
a typical time resolution of about 60 ps. This makes MRPC an optimal choice for
the time of flight(ToF) system in many large physics experiments. The prior
work on improving the time resolution is mainly focused on altering the
detector geometry, and therefore the improvement of the data analysis algorithm
has not been fully explored. This paper proposes a new time reconstruction
algorithm based on the deep neural networks(NN) and improves the MRPC time
resolution by about 10 ps. Since the development of the high energy physics
experiments has pushed the timing requirements for the MRPC to a higher level,
this algorithm could become a potential substitution of the time over
threshold(ToT) method to achieve a time resolution below 30 ps.
