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RESEARCH PAPER · Electronics · 2023

Fast Prediction Method of Combustion Chamber Parameters Based on Artificial Neural Network

Chenhuzhe Shao, Yue Liu, Zhedian Zhang, Fulin Lei, Jinglun Fu

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8 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
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42 direct citing works

Fast Prediction Method of Combustion Chamber Parameters Based on Artificial Neural NetworkOriginalHyperparameter Optimization with Genetic Algorithms and XGBoost: A Step Forward in Smart Grid Fraud Detection84AI-driven DfAM of aeronautical hydrogen gas turbine combustors10Modeling of heavy-duty gas turbine based on machine learning algorithms0A Novel Power Prediction Model Based on the Clustering Modification Method for a Heavy-Duty Gas Turbine1NEURAL NETWORK ACCELERATION OF NUMERICAL SIMULATION OF METHANE COMBUSTION IN A GAS TURBINE ENGINE0Comparative Evaluation of Deep Learning Graph Neural Networks and Classical Machine Learning Models for Predicting Heats of Combustion as a Key Hazard Indicator under GHS/CLP Standards0Revolutionizing gas turbine performance analysis with deep learning powered digital twin0Progress of machine learning in computational fluid dynamics combustion simulation0

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  1. Hyperparameter Optimization with Genetic Algorithms and XGBoost: A Step Forward in Smart Grid Fraud Detection

    Sensors · 2024-02-15

    Adil Mehdary, Abdellah Chehri, Abdeslam Jakimi, Rachid Saadane

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  2. AI-driven DfAM of aeronautical hydrogen gas turbine combustors

    International Journal of Hydrogen Energy · 2024-06-20

    Alberto A. Boretti, Aijun J. Huang

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  3. Modeling of heavy-duty gas turbine based on machine learning algorithms

    International Workshop on Automation, Control, and Communication Engineering (IWACCE) · 2024-12-30

    Wenjiang Huang, Jie Wang, Yingjie Li, Fang Zhang, Haiming Jiang

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  4. A Novel Power Prediction Model Based on the Clustering Modification Method for a Heavy-Duty Gas Turbine

    Applied Sciences · 2025-01-05

    Jing Kong, Wei Yu, Jinwei Chen, Huisheng Zhang

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  5. NEURAL NETWORK ACCELERATION OF NUMERICAL SIMULATION OF METHANE COMBUSTION IN A GAS TURBINE ENGINE

    Eurasian Physical Technical Journal · 2025-12-29

    A.V. Chepurnyi, Andris Jakovičs

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  6. Comparative Evaluation of Deep Learning Graph Neural Networks and Classical Machine Learning Models for Predicting Heats of Combustion as a Key Hazard Indicator under GHS/CLP Standards

    ACS Omega · 2026-03-16

    Osita Sunday Nnyigide, Haewon Byeon, Uchenna Esther Okpete

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  7. Revolutionizing gas turbine performance analysis with deep learning powered digital twin

    e-Prime – Nexus of Electrical Electronic and Intelligent Engineering · 2026-04-03

    Balbir Shah Mohd Irwan Shah, Asnor Juraiza Ishak, Mohd Khair Hassan, Nor Mohd Haziq Norsahperi

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  8. Progress of machine learning in computational fluid dynamics combustion simulation

    Journal of the Energy Institute · 2026-04-15

    Yingqi Zhao, Xinying Wu, Yuhao Li, Fan Hu, Chong Ma, Qiang Liu, Chuan Zhang, Xingyu Lou, Qingyang Peng, Haohua Liao, Kaihua Lu, Bo Li

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