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

Gas sensor drift has consistently been a bottleneck in the progression of electronic noses (E-noses) systems. In contrast to target-domain-adaptive anti-drift classification algorithms, target-domain-free methods exhibit independence from target domain information, thereby possessing broader applicability. Support vector machine (SVM), as a popular target-domain-free classifier, is widely employed to solve the E-noses drift problem. However, SVM-based methods have some inherent flaws in drift resistance performance: (1) The objective of maximizing minimum margin, rendering it highly sensitive to disturbances; (2) The utilization of hinge loss, resulting in poor robustness; (3) The absence of sample reliability measurement, contributing to noise susceptibility. To tackle these problems, we present a novel twin-center intuitionistic fuzzy large margin classifier with unified pinball loss (TC-IFUPLMC), which effectively improves the anti-drift performance in E-noses system. Specifically, the model achieves strong disturbance resistance by adopting marginal mean and variance as the optimization objective. Furthermore, the unified pinball loss is utilized to measure the distance between two categories of sample sets, which essentially further enhances the robustness. Additionally, a novel twin-center based IF function is used to obtain the confidence level of each sample, which further weakens the noise susceptibility. Comparative experiments based on different sensor drift datasets demonstrate the effectiveness of the proposed model in improving the anti-drift performance. The high stability of TC-IFUPLMC is also substantiated by the parameter sensitivity analysis experiments. • An effective target-domain-free TC-IFUPLMC model is proposed. • TC-IFUPLMC is the first LDM-based model to solve electronic noses drift. • TC-IFUPLMC sensibly enhances the anti-drift performance in electronic noses system. • TC-IFUPLMC has superior disturbance resistance, robustness, and noise resistance. [ABSTRACT FROM AUTHOR]