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Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. (2025)
Journal Article
AMINAHO, E.N., AMINAHO, N.S., HOSSAIN, M., FAISAL, N.H. and AMINAHO, K.A. 2025. Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. Gas science and engineering [online], 134, article number 205546. Available from: https://doi.org/10.1016/j.jgsce.2025.205546

The concentration of gases in gas streams can be monitored using sensors. However, gas sensors can lose their response accuracy due to mechanical wear or damage, and environmental factors such as exposure to unusual temperature and pressure condition... Read More about Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage..

Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset] (2025)
Data
AMINAHO, E.N., AMINAHO, N.S., HOSSAIN, M., FAISAL, N.H. and AMINAHO, K.A. 2025. Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset]. Gas science and engineering [online], 134, article number 205546. Available from: https://doi.org/10.1016/j.jgsce.2025.205546

This study proposed a new sensor calibration methodology and the design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams. Furthermore, machine learning models were developed in this study to explore... Read More about Design of a hybrid artificial intelligence system for real-time quantification of impurities in gas streams: application in CO2 capture and storage. [Dataset].