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. |
وضعیت: پذیرفته شده برای ارائه شفاهی |