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15 May 2023 Ensemble kernel-based broad learning system for fast gas recognition in electronic nose systems
Wang Li, LinJu Zhao, Shun Wang
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Proceedings Volume 12699, Third International Conference on Sensors and Information Technology (ICSI 2023); 126990C (2023) https://doi.org/10.1117/12.2678981
Event: International Conference on Sensors and Information Technology (ICSI 2023), 2023, Xiamen, China
Abstract
The rapid recognition of flammable and toxic gases is an essential and challenging task for electronic noses (E-nose) in various fields. The traditional recognition method is limited by the limited features of the gas ultra-time response curve, and has the problems of unsatisfactory classification results and long recognition time. We propose a noval gas recognition algorithm that combines the ensemble learning method with kernel-base learning system learning (KBLS), thereby improving the accuracy of gas recognition, with faster recognition time, and a more stable model. We used four volatile combustible gases as gas test datasets and evaluated the algorithm proposed in this study over a range of response curves from 0.5s to 4s. According to our extensive comparative experiments, it is found that the accuracy is higher than that of other algorithms.
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Wang Li, LinJu Zhao, and Shun Wang "Ensemble kernel-based broad learning system for fast gas recognition in electronic nose systems", Proc. SPIE 12699, Third International Conference on Sensors and Information Technology (ICSI 2023), 126990C (15 May 2023); https://doi.org/10.1117/12.2678981
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KEYWORDS
Machine learning
Detection and tracking algorithms
Matrices
Sensors
Data modeling
Classification systems
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