Hand gestures are crucial for developing prosthetic and rehabilitation devices, enabling
intuitive human–computer interaction (HCI) and improving accessibility for individuals with …

Partial least squares (PLS) model is the most typical data-driven method for quality-related
industrial tasks like soft sensor. However, only linear relations are captured between the …

In high-dimensional data classification, effectively extracting discriminative features while
eliminating redundancy is crucial for enhancing the performances of classifiers, such as …

The classical linear discriminant analysis (LDA) algorithm has three primary drawbacks, ie,
small sample size problem, sensitivity to noise and outliers, and inability to deal with multi …

Linear discriminant analysis (LDA) and its variants are popular supervised dimension
reduction methods, which have been widely used to handle high-dimensional data. Since …

Dimensionality reduction methods for images directly without matrix-to-vector conversion
have been widely concerned and achieved good classification results, especially for face …

To enhance the fault diagnosis capability for ultrasonic liquid flow meters and refine the fault
diagnosis accuracy of support vector machines, we employ Levy flight to augment the global …

In an age marked by an unprecedented influx of data across diverse domains, the quest for
effective machine learning (ML) solutions has increased significantly. However, data …

Based on the theories of Riemannian surface, Topology and Analytic function, a novel
method for dimensionality reduction is proposed in this paper. This approach utilizes FCA to …

Sensor-based sorting (SBS) is a mineral concentration process where rocks or bulk
materials are separated based on their differential sensor responses. SBS is essential in …