Concurrent analytics of temporal information and local correlation for meticulous quality prediction of industrial processes

Recursive cointegration analytics for adaptive monitoring of nonstationary industrial processes with both static and dynamic variations

(2020) Wanke Yu et al.   JOURNAL OF PROCESS CONTROL

A new soft-sensor algorithm with concurrent consideration of slowness and quality interpretation for dynamic chemical process

(2019) Yan Qin et al.   CHEMICAL ENGINEERING SCIENCE

Robust Monitoring and Fault Isolation of Nonlinear Industrial Processes Using Denoising Autoencoder and Elastic Net

(2019) Wanke Yu et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Supervised Variational Autoencoders for Soft Sensor Modeling With Missing Data

(2019) Ruimin Xie et al.   IEEE Transactions on Industrial Informatics

Broad Convolutional Neural Network Based Industrial Process Fault Diagnosis With Incremental Learning Capability

(2019) Wanke Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Hierarchical Quality-Relevant Feature Representation for Soft Sensor Modeling: A Novel Deep Learning Strategy

(2019) Xiaofeng Yuan et al.   IEEE Transactions on Industrial Informatics

Are discoveries spurious? Distributions of maximum spurious correlations and their applications

(2018) Jianqing Fan et al.   ANNALS OF STATISTICS

Ensemble deep kernel learning with application to quality prediction in industrial polymerization processes

(2018) Yi Liu et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Sparse Exponential Discriminant Analysis and Its Application to Fault Diagnosis

(2018) Wanke Yu et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture

(2018) C. L. Philip Chen et al.   IEEE Transactions on Neural Networks and Learning Systems

A Data-Driven Soft Sensor Modeling Method Based on Deep Learning and its Application

(2017) Weiwu Yan et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Variable selection in multi-block regression

(2016) Alessandra Biancolillo et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Review of soft sensor methods for regression applications

(2016) Francisco A.A. Souza et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images

(2016) Jun Xu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Probabilistic Fault Diagnosis Based on Monte Carlo and Nested-Loop Fisher Discriminant Analysis for Industrial Processes

(2016) Chunhui Zhao et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Probabilistic slow feature analysis-based representation learning from massive process data for soft sensor modeling

(2015) Chao Shang et al.   AICHE JOURNAL

PCANet: A Simple Deep Learning Baseline for Image Classification?

(2015) Tsung-Han Chan et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Granger Causality Analysis in Neuroscience and Neuroimaging

(2015) A. K. Seth et al.   JOURNAL OF NEUROSCIENCE

Deep learning

(2015) Yann LeCun et al.   NATURE

Quality prediction and analysis for large-scale processes based on multi-level principal component modeling strategy

(2014) Zhiqiang Ge   CONTROL ENGINEERING PRACTICE

Data-driven soft sensor development based on deep learning technique

(2014) Chao Shang et al.   JOURNAL OF PROCESS CONTROL

Adaptive soft sensor for online prediction and process monitoring based on a mixture of Gaussian process models

(2013) Ratko Grbić et al.   COMPUTERS & CHEMICAL ENGINEERING

The MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference

(2013) Lionel Barnett et al.   JOURNAL OF NEUROSCIENCE METHODS

Integrated soft sensor using just-in-time support vector regression and probabilistic analysis for quality prediction of multi-grade processes

(2013) Yi Liu et al.   JOURNAL OF PROCESS CONTROL

Training restricted Boltzmann machines: An introduction

(2013) Asja Fischer et al.   PATTERN RECOGNITION

A Bayesian inference based two-stage support vector regression framework for soft sensor development in batch bioprocesses

(2012) Jie Yu   COMPUTERS & CHEMICAL ENGINEERING

Local learning-based adaptive soft sensor for catalyst activation prediction

(2010) Petr Kadlec et al.   AICHE JOURNAL

Data-driven Soft Sensors in the process industry

(2009) Petr Kadlec et al.   COMPUTERS & CHEMICAL ENGINEERING

Development of a new soft sensor method using independent component analysis and partial least squares

(2008) Hiromasa Kaneko et al.   AICHE JOURNAL