(LStm),
models
are
able
to
efficiently
handle
long-term
dependencies
in
time
series
data,
which
is
crucial
for
applications
such
as
language
translation
and
time
series
prediction。
得益于長短期記憶網(wǎng)絡(luò)(LStm)這種特殊類型的RNN算法,模型能夠高效處理時間序列數(shù)據(jù)中的長期依賴關(guān)系,這在語言翻譯和時間序列預(yù)測等應(yīng)用中至關(guān)重要。
the
development
of
generative