Abstracts Nowadays, many researchers utilize cancer gene expression data to solve the
problem of cancer subtype diagnosis, but cancer gene expression data are often high-…

In the process of modern industrial production, soft sensing technology is often used to predict
the target variables that are difficult to be directly measured by hard instruments. However, …

In modern industrial production processes, hard instruments are often used to measure
quality variables in industrial processes, but they are often subject to various economic or …

In the process of modern industrial production, it is difficult to realize real-time monitoring
effectively because of economic or technical constraints. To mitigate these problems, soft …

To prevent potential dangers, it is crucial to accurately predict the Remaining Useful Life (RUL)
of Lithium-Ion Batteries (LIBs) as capacity gradually decreases during use. Based on the …

Lithium-ion batteries play a crucial role in our daily lives. Accurately predicting the State of
Health (SOH) and Remaining Useful Life of lithium-ion batteries is essential. To solve the …

Soft-sensor technology predicts quality variables hard for hard instruments to measure
directly, but input variables have redundancy. Thus, feature selection is needed to reduce data …

The primary challenge in diagnosing cancer subtypes lies in the high dimensionality and
sample imbalance of cancer gene expression data, which complicates accurate diagnosis from …

Simulated Moving Bed (SMB) chromatography separation is a novel absorptive separation
technique with high separation capacity, and it is challenging to make the process run stably …

By removing irrelevant or redundant features, feature selection helps simplify the model and
avoid over-fitting while preserving the core information of the data. In recent years, …