@inproceedings{1eabdbaeab8c46ec947610fbada0c0d1,
title = "Lateral jet force model identification based on FCM-SVM",
abstract = "To describe the lateral jet force model accurately, an identification method based on FCM-SVM is provided. The experimental data is clustered with this method to gain the best partition and separating hyperplanes. Different classes are identified respectively using maximum-likelihood estimation method. The test data is classified through separating hyperplanes. The output of test data can be forecasted according to the expression of corresponding class. Result shows that the precision is increased by 31\% compared with traditional identification model. The identification result based on FCM-SVM can supply support for the design of control system.",
keywords = "FCM, Identification, Lateral jet, Model, SVM",
author = "Xiaofeng Liu and Yunfeng Dong and Xiaolei Wang",
year = "2012",
doi = "10.1007/978-1-4471-2467-2\_42",
language = "英语",
isbn = "9781447124665",
series = "Lecture Notes in Electrical Engineering",
pages = "363--369",
booktitle = "Electrical, Information Engineering and Mechatronics 2011 - Proceedings of the 2011 International Conference on Electrical, Information Engineering and Mechatronics, EIEM 2011",
note = "2011 International Conference on Electrical, Information Engineering and Mechatronics, EIEM 2011 ; Conference date: 23-12-2011 Through 25-12-2011",
}