TS Fuzzy Identification for Mathematical Modeling of HIV Infection
کد مقاله : 1247-CFIS
نویسندگان:
محمد تشنه لب *1، آرزو وفامند2، علیرضا فاتحی3
1دانشگاه خواجه نصیرالدین طوسی
2دانشگاه خواجه نصیرالدین طوسی، تهران، ایران
3برق کنترل-برق- دانشگاه خواجه نصیر-تهران-ایران
چکیده مقاله:
Identifying a system and estimating a
model based on Input-Output data is a very important
process because many engineering method and
solutions depend on the model. In this paper, the
problem of nonlinear Takagi-Sugeno (TS) fuzzy
system identification of the HIV infection disease is
investigated. TS fuzzy system with input-output
representation is considered and the parameters of
the consequent part are computed based on the least
square (LS) and gradient descend (GD) methods.
Meanwhile, Gaussian fuzzy membership functions
are utilized in the premise part. Furthermore, based
on the practical restrictions and response of the HIV
disease, a proper pseudo-random binary sequence
(PRBS) input signal is proposed. Numerical
simulation results show the accuracy of the TS fuzz
کلیدواژه ها:
Takagi-Sugeno (TS) fuzzy system, HIV infection disease, fuzzy System identification, Least square, Gradient descend.
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