Integrated neural-network-based method for predicting synthetic permeability in lead-zinc sintering process

Xu Chen-Hua, Wu Min, She Jin-Hua, Yokoyama Ryuichi

研究成果: Conference contribution

抄録

In order to deal with the time variance and strong nonlinearity of lead-zinc sinteringprocess, an integrated method of predicting synthetic permeability based on neural networks (NNs) and a particle swarm algorithm has been developed. In this paper, the concept of the exponent of synthetic permeability, which reflects the state of the permeability of the process, is first explained. Next, NNs are used to establish timesequence- based and technological-parameter-based models for predicting the permeability. Then, an integrated structure based on a fuzzy classifier is described and used to construct an intelligent integrated model for predicting the permeability that combines the two models just mentioned. Finally, the results of actual runs show the method to be both effective and practical.

本文言語English
ホスト出版物のタイトル2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008
DOI
出版ステータスPublished - 2008
イベント2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008 - London
継続期間: 2008 9 92008 9 10

Other

Other2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008
CityLondon
Period08/9/908/9/10

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信

フィンガープリント

「Integrated neural-network-based method for predicting synthetic permeability in lead-zinc sintering process」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル