LS-SVM modeling simulation for the calcination process of lithopone
被引:0
作者:
Zhu, Yan-Fei
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h-index: 0
机构:
Coll. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, ChinaColl. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, China
Zhu, Yan-Fei
[1
]
Mao, Zong-Yuan
论文数: 0引用数: 0
h-index: 0
机构:
Coll. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, ChinaColl. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, China
Mao, Zong-Yuan
[1
]
Tan, Guang-Xing
论文数: 0引用数: 0
h-index: 0
机构:
Coll. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, ChinaColl. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, China
Tan, Guang-Xing
[1
]
机构:
[1] Coll. of Automat. Sci. and Eng., South China Univ. of Technol., Guangzhou 510640, China
来源:
Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
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2004年
/
32卷
/
11期
关键词:
Computer simulation - Models - Vectors;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
In order to overcome the difficulty in the modeling of lithopone calcination, an identification algorithm based on the LS-SVM (Least Squares Support Vector Machine) was applied to the modeling of the calcination process. As the LS-SVM algorithm is of the advantages of simple structure and high speed, according to the mechanisms of SVM and LS-SVM algorithms, a model describing the variation of rotating speed with the temperature in the calcinations process was obtained by modeling simulation. The identification performance of the proposed algorithm was finally compared with that of the ANFIS (Adaptive Neural-fuzzy Inference System), with the conclusion that the LS-SVM is more valuable when applied to the modeling of the calcination process.