Multiclass data classification using fault detection-based techniques

Multivariate fault detection and classification using interval principal component analysis

Generalized low-density (GLD) lattices

Bayesian-optimized Gaussian process-based fault classification in industrial processes

Quantified database for methane dehydroaromatization reaction

Fault detection of single and interval valued data using statistical process monitoring techniques

Bayesian optimization of multiscale kernel principal component analysis and its application to model Gas-to-liquid (GTL) process data

Bayesian-optimized Neural Networks and their application to model gas-to-liquid plants

Multiscale Bayesian PCA for robust process modeling of a Fischer–Tropsch bench scale process

A Data-Driven Framework for Monitoring the Operation of Gas-to-Liquid (GTL) Plants

Data-Driven Process Monitoring of Gas-to-Liquid Plants

A Practical Application of Detection-Based Multiclass Classification of Faults: Tennessee Eastman Process

Application of a fuzzy learning intervention approach to a purine metabolism pathway model

Application of a fuzzy learning intervention approach to a Glycolytic-Glycogenolytic pathway model