Ensemble independent component regression models and soft sensing application

Zhiqiang Ge; Zhihuan Song

doi:10.1016/j.chemolab.2013.09.009

ScienceGate Book Chapters

JOURNAL ARTICLE

Ensemble independent component regression models and soft sensing application

Zhiqiang Ge Zhihuan Song

Year: 2013 Journal: Chemometrics and Intelligent Laboratory Systems Vol: 130 Pages: 115-122 Publisher: Elsevier BV

DOI: 10.1016/j.chemolab.2013.09.009

Get Full-Text PDF Get Analytical Report

Keywords:

Subspace topology Ensemble forecasting Component (thermodynamics) Ensemble learning Computer science Soft sensor Artificial intelligence Process (computing) Data mining Gaussian process Machine learning Gaussian Pattern recognition (psychology)

Metrics

Cited By

7.32

FWCI (Field Weighted Citation Impact)

Refs

0.97

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Spectroscopy and Chemometric Analyses

Physical Sciences → Chemistry → Analytical Chemistry

Mineral Processing and Grinding

Physical Sciences → Engineering → Mechanical Engineering

Ensemble independent component regression models and soft sensing application

Metrics

Citation History

Topics

Related Documents

Soft sensing of non-Gaussian processes using ensemble modified independent component regression

Quality-relevant independent component regression model for virtual sensing application

A subspace ensemble regression model based slow feature for soft sensing application

Adaptive Selective Ensemble-Independent Component Analysis Models for Process Monitoring

Application of Independent Component Regression in Dam Deformation Analysis