@inproceedings{20c7adb98bc141eb85d50d89db96d610,

title = "A fuzzy neural network approach to model component behavior for virtual prototyping of hydraulic system",

abstract = "This paper proposes a fuzzy neural network (FNN) approach to model the behavior of a hydraulic component from input-output data. The approach uses an {"}effect{"} variable, which can be used to identify the significant inputs from the input-output data. The variations of the {"}effects{"} of the significant inputs are used to determine the number of fuzzy rules and the structure of the network. The proposed approach can be used to effectively map the input to output behavior of a hydraulic pressure control system. This is useful for virtual prototyping of fluid power systems.",

keywords = "Fluid power system, Fuzzy neural network (FNN)",

author = "Wei Xiang and Fok, {Sai Cheong} and Yap, {Fook Fah}",

year = "2001",

month = mar,

day = "1",

doi = "10.1145/372202.372426",

language = "English",

isbn = "1581132875",

volume = "Part F129805",

series = "Proceedings of the ACM Symposium on Applied Computing",

publisher = "Association for Computing Machinery",

pages = "482--483",

booktitle = "Proceedings of the 2001 ACM Symposium on Applied Computing, SAC 2001",

note = "2001 ACM Symposium on Applied Computing, SAC 2001 ; Conference date: 11-03-2001 Through 14-03-2001",

}