Shigeto Suzuki
,
Michiko Hiraoka
,
Takashi Shiraishi
,
Enxhi Kreshpa
,
Takuji Yamamoto
,
Hiroyuki Fukuda
,
Shuji Matsui
,
Masahide Fujisaki
,
Atsuya Uno
… In this work, we report a state-of-the-art power prediction model. … Conventional methods with topic model use the power of past job as a prediction based on the similarity of job information. … To resolve this, we developed a recurrent neural network model with variable network size, which detects features of power shape from its power history and enables precise prediction during job execution. …
IPSJ