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

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

Developing accurate data-driven soft-sensors through integrating dynamic kernel slow feature analysis with neural networks

(2021) Jeremiah Corrigan et al.   JOURNAL OF PROCESS CONTROL

Novel double layer BiLSTM minor soft fault detection for sensors in air-conditioning system with KPCA reducing dimensions

(2021) Xiuying Yan et al.   Journal of Building Engineering

Novel Discriminant Locality Preserving Projection Integrated With Monte Carlo Sampling for Fault Diagnosis

(2021) Yan-Lin He et al.   IEEE TRANSACTIONS ON RELIABILITY

Novel soft sensor development using echo state network integrated with singular value decomposition: Application to complex chemical processes

(2020) Yan-Lin He et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

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

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

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

Persistent impulsive effects on stability of functional differential equations with finite or infinite delay

(2018) Xiaodi Li et al.   APPLIED MATHEMATICS AND COMPUTATION

A novel recurrent neural network soft sensor via a differential evolution training algorithm for the tire contact patch

(2017) Carlos A. Duchanoy et al.   NEUROCOMPUTING

Adaptive soft sensor for quality prediction of chemical processes based on selective ensemble of local partial least squares models

(2015) Weiming Shao et al.   CHEMICAL ENGINEERING RESEARCH & DESIGN

Adaptive soft sensor based on online support vector regression and Bayesian ensemble learning for various states in chemical plants

(2014) Hiromasa Kaneko et al.   CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS

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

Data-driven Soft Sensors in the process industry

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