@inproceedings{e01513a193844832a979c975cb01f0c2,
title = "Intelligent control for moisture of sinter mixture based on ABPM artificial neural network",
abstract = "The moisture control for sinter mixture is always a difficulty in industry. This paper presents a modeling for the Pb-Zn sintering process of Imperial Smelting Process(ISP), which is to solve the modeling of permeability and parameters of sintering technical. An intelligent system for controlling moisture of sinter mixture based on ABPM artificial neural network is developed for the purpose. The BP network is trained by adaptive variable step size algorithm in order to get high accuracy and fast convergence speed. Theoretical research and simulation verify the effectiveness of the proposed method.",
keywords = "Adaptive variable step size algorithm, Artificial neural network, Moisture of mixture, Permeability",
author = "Guo Li and Guangming Zhang and Xiang Ling and Weihua Gui and Guizhong Tang",
year = "2008",
doi = "10.1109/WCICA.2008.4594295",
language = "英语",
isbn = "9781424421145",
series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",
pages = "8671--8675",
booktitle = "Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08",
note = "7th World Congress on Intelligent Control and Automation, WCICA'08 ; Conference date: 25-06-2008 Through 27-06-2008",
}