Research on performance prediction of gas turbine air filtration system based on transformation-gated LSTM method-Reference-Cited by-同舟云学术

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Research on performance prediction of gas turbine air filtration system based on transformation-gated LSTM method

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 2nd International Conference on Electronics, Communications and Information Technology (CECIT)
language:
Short-container-title:

Author:

Yao Jiachi¹,Liu Chao¹,Hao Jiangang²,Huang Haizhou²,Deng Gaofeng³,Jiang Dongxiang¹

Affiliation:

1. Tsinghua University,Department of Energy and Power Engineering,Beijing,China

2. HuaDian Electric Power Research Institute Co., Ltd.,Hangzhou,China

3. State Key Laboratory of Building Safety and Environment, China Academy of Building Research,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9741750/9741857/09741858.pdf?arnumber=9741858

Reference25 articles.

1. Gas turbine performance prediction via machine learning

2. Gas turbine monitoring using neural network dynamic nonlinear autoregressive with external exogenous input modelling

3. Fault detection and isolation of gas turbine using series–parallel NARX model

4. Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

5. A Novel Framework for Machine Remaining Useful Life Prediction Based on Time Series Analysis

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