Prediction of Endpoint Sulfur Content in KR Desulfurization Based on the Hybrid Algorithm Combining Artificial Neural Network With SAPSO

Prediction of Endpoint Sulfur Content in KR Desulfurization Based on the Hybrid Algorithm Combining Artificial Neural Network With SAPSO

In the present work, the endpoint sulfur content prediction model of Kambara Reactor (KR) desulfurization in the steelmaking process is investigated. For Artificial Neural Network (ANN), the effects of different structure parameters, including the number of hidden layer neurons, activation functions...

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Bibliographic Details
Main Authors: Siwei Wu, Jian Yang, Runhao Zhang, Hideki Ono
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Artificial neural network
particle swarm optimization
multiple linear regression
prediction of endpoint sulfur content
KR desulfurization process
Online Access:https://ieeexplore.ieee.org/document/8982000/

Internet

https://ieeexplore.ieee.org/document/8982000/

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