A classification-driven neuron-grouped SAE for feature representation and its application to fault classification in chemical processes

Multimodal Process Monitoring Based on Variational Bayesian PCA and Kullback-Leibler Divergence between Mixture Models

(2021) Yue Cao et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

Intelligent fault diagnosis of rotating machinery based on continuous wavelet transform-local binary convolutional neural network

(2021) Yiwei Cheng et al.   KNOWLEDGE-BASED SYSTEMS

Deep sparse autoencoder prediction model based on adversarial learning for cross-domain recommendations

(2021) Yakun Li et al.   KNOWLEDGE-BASED SYSTEMS

Hierarchical hybrid distributed PCA for plant-wide monitoring of chemical processes

(2021) Yue Cao et al.   CONTROL ENGINEERING PRACTICE

Deep learning for fault-relevant feature extraction and fault classification with stacked supervised auto-encoder

(2020) Yalin Wang et al.   JOURNAL OF PROCESS CONTROL

Knowledge extraction and insertion to deep belief network for gearbox fault diagnosis

(2020) Jianbo Yu et al.   KNOWLEDGE-BASED SYSTEMS

ASRNN: A recurrent neural network with an attention model for sequence labeling

(2020) Jerry Chun-Wei Lin et al.   KNOWLEDGE-BASED SYSTEMS

Hybrid artificial neural network and cooperation search algorithm for nonlinear river flow time series forecasting in humid and semi-humid regions

(2020) Zhong-kai Feng et al.   KNOWLEDGE-BASED SYSTEMS

Rolling bearing fault diagnosis using optimal ensemble deep transfer network

(2020) Xingqiu Li et al.   KNOWLEDGE-BASED SYSTEMS

Evolutionary manifold regularized stacked denoising autoencoders for gearbox fault diagnosis

(2019) Jian-Bo Yu   KNOWLEDGE-BASED SYSTEMS

A novel deep learning based fault diagnosis approach for chemical process with extended deep belief network

(2019) Yalin Wang et al.   ISA TRANSACTIONS

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

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

Deep convolutional neural network model based chemical process fault diagnosis

(2018) Hao Wu et al.   COMPUTERS & CHEMICAL ENGINEERING

Multivariate Statistical Monitoring of Key Operation Units of Batch Processes Based on Time-Slice CCA

(2018) Qingchao Jiang et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY

Deep Learning-Based Feature Representation and Its Application for Soft Sensor Modeling With Variable-Wise Weighted SAE

(2018) Xiaofeng Yuan et al.   IEEE Transactions on Industrial Informatics

Multi-similarity measurement driven ensemble just-in-time learning for soft sensing of industrial processes

(2018) Xiaofeng Yuan et al.   JOURNAL OF CHEMOMETRICS

Dendritic Neuron Model With Effective Learning Algorithms for Classification, Approximation, and Prediction

(2018) Shangce Gao et al.   IEEE Transactions on Neural Networks and Learning Systems

Recent Advances in Key-Performance-Indicator Oriented Prognosis and Diagnosis With a MATLAB Toolbox: DB-KIT

(2018) Yuchen Jiang et al.   IEEE Transactions on Industrial Informatics

Quality Relevant and Independent Two Block Monitoring Based on Mutual Information and KPCA

(2017) Junping Huang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Dimension reduction based on a penalized kernel support vector machine model

(2017) He Jiang et al.   KNOWLEDGE-BASED SYSTEMS

Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

(2016) Qingchao Jiang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network

(2016) Peng Jiang et al.   SENSORS

Improved PLS Focused on Key-Performance-Indicator-Related Fault Diagnosis

(2015) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Single Sample Face Recognition via Learning Deep Supervised Autoencoders

(2015) Shenghua Gao et al.   IEEE Transactions on Information Forensics and Security

Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships

(2015) Junshui Ma et al.   Journal of Chemical Information and Modeling

A Review on Basic Data-Driven Approaches for Industrial Process Monitoring

(2014) Shen Yin et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Comparative evaluation of classification methods used in fault diagnosis of industrial processes

(2013) Alberto Prieto Moreno et al.   IEEE Latin America Transactions

From Model, Signal to Knowledge: A Data-Driven Perspective of Fault Detection and Diagnosis

(2013) Xuewu Dai et al.   IEEE Transactions on Industrial Informatics

Nonlinear Projection Trick in Kernel Methods: An Alternative to the Kernel Trick

(2013) Nojun Kwak   IEEE Transactions on Neural Networks and Learning Systems

A comparison study of basic data-driven fault diagnosis and process monitoring methods on the benchmark Tennessee Eastman process

(2012) Shen Yin et al.   JOURNAL OF PROCESS CONTROL

Generalized Reconstruction-Based Contributions for Output-Relevant Fault Diagnosis With Application to the Tennessee Eastman Process

(2010) Gang Li et al.   IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY