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RESEARCH PAPER · Industrial & Engineering Chemistry Research · 2021

Data-Driven Prediction of Minimum Fluidization Velocity in Gas-Fluidized Beds Using Data Extracted by Text Mining

Jibin Zhou, Duiping Liu, Mao Ye, Zhongmin Liu

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Data-Driven Prediction of Minimum Fluidization Velocity in Gas-Fluidized Beds Using Data Extracted by Text MiningOriginalTowards a general correlation for minimum fluidization velocity in gas-fluidized beds: Based on a database mining from the literature4Machine Learning Approach to Predict the Surface Charge Density of Monodispersed Particles in Gas–Solid Fluidized Beds11An Open Data Repository for Engineering Design: Using Text Mining with Open Government Data12The accurate prediction and analysis of bed expansion characteristics in liquid–solid fluidized bed based on machine learning methods25Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors294100 years of scaling up fluidized bed and circulating fluidized bed reactors91Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture46Machine Learning and Data-Driven Modeling to Discover the Bed Expansion Ratio Correlation for Gas–Liquid–Solid Three-Phase Flows14Text Mining-based Enterprise Financial Performance Evaluation in the Context of Enterprise Digital Transformation1Binary mixtures of biomass and inert components in fluidized beds: Experimental and neural network exploration8Development of Effective Voidage Correlations in Pilot-Scale Liquid–Solid Fluidized Bed Based on Data-Driven Modeling5Improving the precision of solids velocity measurement in gas-solid fluidized beds with a hybrid machine learning model14Construction and Analysis of the Mesoscale Drag Force Model Based on Machine Learning Methods13Physics-informed dynamic mode decomposition for short-term and long-term prediction of gas-solid flows18Pilot-scale pyrolysis and activation of typical biomass chips in an interconnected dual fluidized bed: Comparison and analysis of products15Identification of gas-solid flow regimes using convolutional neural network techniques23Customized Software Package for the Simultaneous Prediction of Multiple Fluidization Characteristic Parameters in Liquid–Solid Fluidized Beds2A data-driven method for fast predicting the long-term hydrodynamics of gas–solid flows: Optimized dynamic mode decomposition with control7A universal drag model for liquid-solid fluidization: Experiment, data-driven modeling, CFD modeling and simulation2Physics-informed dynamic mode decomposition for reconstruction and prediction of dense particulate pipe flows5Scenic Spots Intelligent Development and Cultural Tourism Integration Mechanism Based on Text Data Mining0Symbolic Regression-Dimensionless Learning Data-Driven Coupled Modeling of the Interpretable Bed Expansion Ratio in a Liquid–Solid Fluidized Bed4Reaction process optimization based on interpretable machine learning and metaheuristic optimization algorithms5Discovery of classical gas-solid flow correlations using a reinforcement learning-based symbolic regression framework4RETRACTED: Reshaping MOFs synthesis conditions mining with a dynamic multi-agents framework of large language model5RESEARCH PROGRESS ON BIOFILM CARRIER MATERIALS IN AQUACULTURE WASTEWATER TREATMENT0

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  1. Towards a general correlation for minimum fluidization velocity in gas-fluidized beds: Based on a database mining from the literature

    Chemical Engineering Science · 2022-01-24

    Jibin Zhou, Mao Ye, Zhongmin Liu

    Read original paper ↗ ·

  2. Machine Learning Approach to Predict the Surface Charge Density of Monodispersed Particles in Gas–Solid Fluidized Beds

    ACS Omega · 2022-03-11

    Junyu Lu, Chenlong Duan, Yuemin Zhao

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  3. An Open Data Repository for Engineering Design: Using Text Mining with Open Government Data

    Computers in Industry · 2022-07-05

    Vito Giordano, Elena Coli, Antonella Martini

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  4. The accurate prediction and analysis of bed expansion characteristics in liquid–solid fluidized bed based on machine learning methods

    Chemical Engineering Science · 2022-07-06

    Jian Wei Peng, Wei Sun, Guangming Zhou, Le Xie, Haisheng Han, Yao Xiao

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  5. Review of Machine Learning for Hydrodynamics, Transport, and Reactions in Multiphase Flows and Reactors

    Industrial & Engineering Chemistry Research · 2022-07-07

    Li‐Tao Zhu, Xizhong Chen, Bo Ouyang, Wei‐Cheng Yan, He Lei, Zhe Chen, Zheng‐Hong Luo

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  6. 100 years of scaling up fluidized bed and circulating fluidized bed reactors

    Powder Technology · 2022-08-05

    Jia Wei Chew, Casey Q. LaMarche, Ray A. Cocco

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  7. Machine Learning in the Development of Adsorbents for Clean Energy Application and Greenhouse Gas Capture

    Advanced Science · 2022-10-26

    Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler, Rachel A. Caruso

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  8. Machine Learning and Data-Driven Modeling to Discover the Bed Expansion Ratio Correlation for Gas–Liquid–Solid Three-Phase Flows

    Industrial & Engineering Chemistry Research · 2022-12-28

    Le Xie, Guangming Zhou, Dongdong Wang, Huaifa Wang, Chongwen Jiang

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  9. Text Mining-based Enterprise Financial Performance Evaluation in the Context of Enterprise Digital Transformation

    International Journal of Advanced Computer Science and Applications · 2023-01-01

    Changrong Guo, Jing Xing

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  10. Binary mixtures of biomass and inert components in fluidized beds: Experimental and neural network exploration

    Fuel · 2023-04-19

    Vincenzo Del Duca, Paola Brachi, Riccardo Chirone, Roberto Chirone, Antonio Coppola, Michele Miccio, Giovanna Ruoppolo

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  11. Development of Effective Voidage Correlations in Pilot-Scale Liquid–Solid Fluidized Bed Based on Data-Driven Modeling

    Industrial & Engineering Chemistry Research · 2023-06-15

    Le Xie, Guangming Zhou, Cun‐Shuai Huo, Jiawei He, Zheng‐Hong Luo, Jia Ming Yang

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  12. Improving the precision of solids velocity measurement in gas-solid fluidized beds with a hybrid machine learning model

    Chemical Engineering Science · 2023-12-02

    Hongliang Xiao, Adefarati Oloruntoba, Xiwei Ke, Kaixuan Gao, Linlin Duan, Cenfan Liu, Yongmin Zhang, Junwu Wang

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  13. Construction and Analysis of the Mesoscale Drag Force Model Based on Machine Learning Methods

    Industrial & Engineering Chemistry Research · 2024-01-18

    Yu Zhang, Yaxiong Yu, Xiao Chen, Shaohua Du, Qiang Zhou

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  14. Physics-informed dynamic mode decomposition for short-term and long-term prediction of gas-solid flows

    Chemical Engineering Science · 2024-02-07

    Dandan Li, Bidan Zhao, Shuai Lu, Junwu Wang

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  15. Pilot-scale pyrolysis and activation of typical biomass chips in an interconnected dual fluidized bed: Comparison and analysis of products

    Renewable Energy · 2024-03-16

    Chunbao Zhou, Yuanxiang Chen, Xuyang Xing, Lei Chen, Chenglong Liu, Chao Li, Bang Yao, Yingwen Zhang, Jianjun Dai, Yang Liu, Jun Wang, Jie Dong, Yunxiang Li, Dekai Fan, Long Wang, Yan Li

    Read original paper ↗ ·

  16. Identification of gas-solid flow regimes using convolutional neural network techniques

    Powder Technology · 2024-05-15

    Dian Zhang, Bo Ouyang, Zheng‐Hong Luo

    Read original paper ↗ ·

  17. Customized Software Package for the Simultaneous Prediction of Multiple Fluidization Characteristic Parameters in Liquid–Solid Fluidized Beds

    Industrial & Engineering Chemistry Research · 2024-07-05

    Jiawei He, Ruiqi Lei, Le Xie

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  18. A data-driven method for fast predicting the long-term hydrodynamics of gas–solid flows: Optimized dynamic mode decomposition with control

    Physics of Fluids · 2024-10-01

    Dandan Li, Bidan Zhao, Shuai Lu, Junwu Wang

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  19. A universal drag model for liquid-solid fluidization: Experiment, data-driven modeling, CFD modeling and simulation

    Powder Technology · 2024-10-02

    Guangming Zhou, Le Xie

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  20. Physics-informed dynamic mode decomposition for reconstruction and prediction of dense particulate pipe flows

    Physics of Fluids · 2024-11-01

    Zhen Zhang, Ze-Jun Qin, Jing Huo, Yan Zhang, Qingkuan Liu

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  21. Scenic Spots Intelligent Development and Cultural Tourism Integration Mechanism Based on Text Data Mining

    Asian Conference on Artificial Intelligence Technology (ACAIT) · 2024-11-08

    Yang Li, Jing Gao

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  22. Symbolic Regression-Dimensionless Learning Data-Driven Coupled Modeling of the Interpretable Bed Expansion Ratio in a Liquid–Solid Fluidized Bed

    Industrial & Engineering Chemistry Research · 2024-12-31

    Jiawei He, Xinyu Du, Le Xie, Zheng‐Hong Luo

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  23. Reaction process optimization based on interpretable machine learning and metaheuristic optimization algorithms

    Chinese Journal of Chemical Engineering · 2025-03-01

    Dian Zhang, Bo Ouyang, Zheng‐Hong Luo

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  24. Discovery of classical gas-solid flow correlations using a reinforcement learning-based symbolic regression framework

    Chemical Engineering Science · 2025-05-01

    Zhong Xiang, Xi Chen

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  25. RETRACTED: Reshaping MOFs synthesis conditions mining with a dynamic multi-agents framework of large language model

    Transactions of Materials Research · 2026-01-01

    Zuhong Lin, Daoyuan Ren, Kai Ran, Jing Sun, Songlin Yu, Xuefeng Bai, Xiaotian Huang, Haiyang He, Pengxu Pan, Ying Guang Fang, Zhanglin Li, Haipu Li, Jingjing Yao

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  26. RESEARCH PROGRESS ON BIOFILM CARRIER MATERIALS IN AQUACULTURE WASTEWATER TREATMENT

    Acta Hydrobiologica Sinica · 2026-06-01

    Yang LÜ, Feng ZHAO, Kun XIANG, Hao-Feng SUN, Ye TIAN, Zhi-Ying HAN, Zhang-Ying Ye

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