A multi-scale prediction model based on empirical mode decomposition and chaos theory for industrial melt index prediction-Reference-Cited by-同舟云学术

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A multi-scale prediction model based on empirical mode decomposition and chaos theory for industrial melt index prediction

Published:2019-03 Issue: Volume:186 Page:23-32
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Zhang Miao,Zhou Le,Jie Jing,Liu Xinggao

Funder

NSFC-Zhejiang

China Postdoctoral Science Foundation

Zhejiang Provincial Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference50 articles.

1. Statistical data modeling based on partial least squares: application to melt index predictions in high density polyethylene processes to achieve energy-saving operation;Ahmed;Kor. J. Chem. Eng.,2013

2. Industrial polyethylene melt index prediction using ensemble manifold learning-based local model;Liu;J. Appl. Polym. Sci.,2017

3. Melt index prediction with a mixture of Gaussian process regression with embedded clustering and variable selections;Chan;J. Appl. Polym. Sci.,2017

4. Multi-focus image fusion using pulse coupled neural network;Huang;Pattern Recogn. Lett.,2018

5. Multimode process monitoring based on switching autoregressive dynamic latent variable model;Zhou;IEEE Trans. Ind. Electron.,2018

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3. Novel Hybrid Neural Network Modeling Method for Melt Index Industrial Soft Sensor;2023 International Conference on Computer Science and Automation Technology (CSAT);2023-10-06

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