Data for: Application of Cost-Sensitive LSTM in Water Level Prediction for Nuclear Reactor Pressurizer
Published: 13 January 2020| Version 1 | DOI: 10.17632/ndzj97x62x.1
Contributors:
Jin Zhang, Wei Bai, Yang Li, Zhisong Pan, Jun Shen, Cheng Zhao, Xiaolong WangDescription
data: Normalized data sampled from a nuclear power plant simulator, including pressurizer water level and other six parameters according to the transient process of increasing reactor power from 30% to 90%. code: including CSLSTM, LSTM and SVR models in two experiment settings, i.e. global learning setting and local learning setting.
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Nuclear Power Plant