Novel virtual sample generation method based on data augmentation and weighted interpolation for soft sensing with small data

Improving the performance of just-in-time learning based soft sensor through data augmentation

(2022) Xiaoyu Jiang et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

A novel virtual sample generation method based on a modified conditional Wasserstein GAN to address the small sample size problem in soft sensing

(2022) Yan-Lin He et al.   JOURNAL OF PROCESS CONTROL

Soft-sensing of effluent total phosphorus using adaptive recurrent fuzzy neural network with Gustafson-Kessel clustering

(2022) Hongbiao Zhou et al.   EXPERT SYSTEMS WITH APPLICATIONS

Co-training based virtual sample generation for solving the small sample size problem in process industry

(2022) Qun-Xiong Zhu et al.   ISA TRANSACTIONS

A novel multivariate grey model for forecasting periodic oscillation time series

(2022) Yaoguo Dang et al.   EXPERT SYSTEMS WITH APPLICATIONS

Knowledge discovery from noisy imbalanced and incomplete binary class data

(2021) Arjun Puri et al.   EXPERT SYSTEMS WITH APPLICATIONS

Enhanced virtual sample generation based on manifold features: Applications to developing soft sensor using small data

(2021) Yan-Lin He et al.   ISA TRANSACTIONS

Novel virtual sample generation using conditional GAN for developing soft sensor with small data

(2021) Qun-Xiong Zhu et al.   ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

An interpretable data augmentation scheme for machine fault diagnosis based on a sparsity-constrained generative adversarial network

(2021) Liang Ma et al.   EXPERT SYSTEMS WITH APPLICATIONS

PM₂.₅ Monitoring: Use Information Abundance Measurement and Wide and Deep Learning

(2021) Ke Gu et al.   IEEE Transactions on Neural Networks and Learning Systems

Handling the impact of feature uncertainties on SVM: A robust approach based on Sobol sensitivity analysis

(2021) Wahb Zouhri et al.   EXPERT SYSTEMS WITH APPLICATIONS

Vision-Based Monitoring of Flare Soot

(2020) Ke Gu et al.   IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

Novel Virtual Sample Generation Based on Locally Linear Embedding for Optimizing the Small Sample Problem: Case of Soft Sensor Applications

(2020) Qun-Xiong Zhu et al.   INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH

Novel manifold learning based virtual sample generation for optimizing soft sensor with small data

(2020) Xiao-Han Zhang et al.   ISA TRANSACTIONS

A virtual sample generation approach based on a modified conditional GAN and centroidal Voronoi tessellation sampling to cope with small sample size problems: Application to soft sensing for chemical process

(2020) Zhong-Sheng Chen et al.   APPLIED SOFT COMPUTING

Ensemble Meta-Learning for Few-Shot Soot Density Recognition

(2020) Ke Gu et al.   IEEE Transactions on Industrial Informatics

Deep Learning With Spatiotemporal Attention-Based LSTM for Industrial Soft Sensor Model Development

(2020) Xiaofeng Yuan et al.   IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS

Data Augmentation Classifier for Imbalanced Fault Classification

(2020) Xiaoyu Jiang et al.   IEEE Transactions on Automation Science and Engineering

Learning parameters of Bayesian networks from datasets with systematically missing data: A meta–analytic approach

(2019) Jelena Kovačić   EXPERT SYSTEMS WITH APPLICATIONS

Deep Dual-Channel Neural Network for Image-Based Smoke Detection

(2019) Ke Gu et al.   IEEE TRANSACTIONS ON MULTIMEDIA

Data supplement for a soft sensor using a new generative model based on a variational autoencoder and Wasserstein GAN

(2019) Xiao Wang et al.   JOURNAL OF PROCESS CONTROL

Encoding Pose Features to Images With Data Augmentation for 3-D Action Recognition

(2019) Thien Huynh-The et al.   IEEE Transactions on Industrial Informatics

A Layer-Wise Data Augmentation Strategy for Deep Learning Networks and Its Soft Sensor Application in an Industrial Hydrocracking Process

(2019) Xiaofeng Yuan et al.   IEEE Transactions on Neural Networks and Learning Systems

A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry

(2018) Yan-Lin He et al.   ENERGY

A tree-based-trend-diffusion prediction procedure for small sample sets in the early stages of manufacturing systems

(2011) Der-Chiang Li et al.   EXPERT SYSTEMS WITH APPLICATIONS

Utilize bootstrap in small data set learning for pilot run modeling of manufacturing systems

(2007) Tung-I Tsai et al.   EXPERT SYSTEMS WITH APPLICATIONS