A data-driven approach to predict NOx-emissions of gas turbines
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/8241556/8257893/08258056.pdf?arnumber=8258056
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. NOx Emission Predictions in Gas Turbines Through Integrated Data-Driven Machine Learning Approaches;Journal of Energy Resources Technology;2024-04-23
2. Development of an Automatic Pipeline for Data Analysis and Pre-Processing for Data Driven-Based Engine Emission Modeling in a Real Industrial Application;SAE Technical Paper Series;2024-04-09
3. Tabular Machine Learning Methods for Predicting Gas Turbine Emissions;Machine Learning and Knowledge Extraction;2023-08-14
4. Using machine-learning methods in determination of the pipe line gas turbine plant effective power;Proceedings of Higher Educational Institutions. Маchine Building;2023-02
5. Estimation of gas turbine power using linear machine learning methods;THE INTERNATIONAL CONFERENCE ON BATTERY FOR RENEWABLE ENERGY AND ELECTRIC VEHICLES (ICB-REV) 2022;2023
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