A novel twin-center intuitionistic fuzzy large margin classifier with unified pinball loss for improving the performance of E-noses system

Chen, Junlin; Luo, Tao; Yan, Jia; Zhang, Libo

doi:10.1016/j.eswa.2024.123883

Expert Systems with Applications

2024

DOI: 10.1016/j.eswa.2024.123883

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A novel twin-center intuitionistic fuzzy large margin classifier with unified pinball loss for improving the performance of E-noses system

Junlin Chen,

Tao Luo,

Jia Yan

et al.

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Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

Mei,

Peng,

Wang

et al. 2024

Nano-Micro Lett.

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As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area. Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors. It is crucial to choose an appropriate pattern recognition method for enhancing data analysis, reducing errors and improving system reliability, obtaining better classification or gas concentration prediction results. In this review, we analyze the sensing mechanism of cross-sensitivity for chemiresistive gas sensors. We further examine the types, working principles, characteristics, and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays. Additionally, we report, summarize, and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification. At the same time, this work showcases the recent advancements in utilizing these methods for gas identification, particularly within three crucial domains: ensuring food safety, monitoring the environment, and aiding in medical diagnosis. In conclusion, this study anticipates future research prospects by considering the existing landscape and challenges. It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

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Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

Mei,

Peng,

Wang

et al. 2024

Nano-Micro Lett.

View full text Add to dashboard Cite

show abstract

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A novel twin-center intuitionistic fuzzy large margin classifier with unified pinball loss for improving the performance of E-noses system

Cited by 1 publication

References 41 publications

Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

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