Abstract: Hidden Markov models (HMMs) for time-series data analysis are attracting wide interests in industries due to their ability to model the extensively existing dynamics and non-Gaussianities.

Abstract: In industrial soft-sensor modeling, the scarcity and imbalance of process data often lead to overfitting and poor generalization of predictive models. To address these challenges, this ...

Objective: This study aimed to determine optimal sample sizes and the relationships between sample size and dataset-level characteristics over a variety of binary classification algorithms. Methods: A ...