Applications for Predicting Cracking Outlet Temperatures for Ethylene Cracker Furnaces Based on the GAC-BiLSTM-AM Method

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Abstract
In order to achieve a good generalization ability across different prediction tasks and ensure the reliability of prediction results, this paper proposes a GAC-BiLSTM-AM prediction method based on ensemble learning. This method employs a dual-channel convolutional neural network to comprehensively extract and integrate sample features, which are then input into a composite analysis module consisting of a bidirectional long short-term memory, an attention mechanism, and a fully connected layer to achieve in-depth analysis and processing of information, jointly constructing an efficient base learner. Meanwhile, during the parameter iteration tuning process of the base learner, a mistake correction mechanism is introduced to dynamically adjust sample weights in order to correct potential attention biases, and further combined with the gold rush optimizer to optimize the key structural parameters of the model. The application evaluation in multiple benchmark prediction tasks confirms that the GAC-BiLSTM-AM method possesses excellent generalization performance.
Funding Information
  • Guangdong Basic and Applied Basic Research Foundation (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Key Field Special Project of Department of Education of Guangdong Province (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Chinese Academy of Sciences Science and Technology Service Network Program Huangpu special project (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Key Laboratory of Marine Environmental Survey Technology and Application Ministry of Natural Resources P.R. China (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Maoming Science and Technology Project (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Special Fund for Scientific and Technological Innovation Strategy of Guangdong Province (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Projects of PhDs’ Start-up Research of GDUPT (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Key Realm R&D Program of Guangdong Province (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • National Natural Science Foundation of China (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)
  • Natural Science Foundation of Guangdong Province (2022A1515012022, 2023A1515240020, 2023A1515011913, 2024A1515012090, 2023A1515011423, 2024ZDZX1034, STS-HP-202202, MESTA-2022-B001, 210429094551175, 2022DZXHT028, mmkj2020033, 2023011, PDJH2023B0304, PDJH2024A225, 2023bsqd1002, 2023bsqd1013, XJ2022000301, 2021B0707010003, 62273109, 62073090, U22A20221)

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