Soft Sensing of NOx Emissions From Thermal Power Units Based on Adaptive GMM Two-Step Clustering Algorithm and Ensemble Learning-Reference-Cited by-同舟云学术

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Soft Sensing of NOx Emissions From Thermal Power Units Based on Adaptive GMM Two-Step Clustering Algorithm and Ensemble Learning

Published:2023 Issue: Volume:72 Page:1-19
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Dong Ze¹^ORCID,Jiang Wei¹^ORCID,Sun Ming²^ORCID,Zhang Yue²^ORCID

Affiliation:

1. School of Control and Computer Engineering, North China Electric Power University, Beijing, China

2. Hebei Technology Innovation Center of Simulation and Optimized Control for Power Generation, North China Electric Power University, Baoding, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province of China

S&T Program of Hebei Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10135138.pdf?arnumber=10135138

Reference37 articles.

1. A flame imaging based online deep learning model for predicting NOx emissions from an oxy-biomass combustion process

2. Deep Bidirectional Learning Machine for Predicting NOx Emissions and Boiler Efficiency from a Coal-Fired Boiler

3. Auto-encoder-extreme learning machine model for boiler NOx emission concentration prediction

4. A maximum variance cluster algorithm

5. Ensemble Classification and Regression-Recent Developments, Applications and Future Directions [Review Article]

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1. Investigation of the Microscopic Dynamical Behavior and Bridging Mechanism of Cellulose Particles in Insulating Oil;IEEE Transactions on Dielectrics and Electrical Insulation;2024-08

2. A novel hybrid forecasting approach for NOx emission of coal‐fired boiler combined with CEEMDAN and self‐attention improved by LSTM;Asia-Pacific Journal of Chemical Engineering;2024-04-11

3. Carbon Monoxide and Nitrogen Oxide Emissions Analysis: Clustering-Based Approach;Lecture Notes in Networks and Systems;2024

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