Results 161 to 170 of about 62,652 (233)

Hybrid feature selection with novel deep learning model for COVID-19 risk prediction. [PDF]

Sci Rep
P GS, Kathiravan M, Shanthi S, Alqahtani MS, Abbas M, Ayalew F.   +5 more
europepmc   +1 more source

Event-triggered fuzzy neural-network PID control for nonlinear gas-blending processes. [PDF]

Sci Rep
Dong W, Wang S, Zhang Z.
europepmc   +1 more source

Prediction of thaw settling coefficient of frozen soil using machine learning techniques. [PDF]

Sci Rep
Wang K, Liu S, Xing W, Zhang L, Tian S, Qiu M, Li S.   +6 more
europepmc   +1 more source

Design and development of a model for tennis elbow injury prediction and prevention using Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) approaches. [PDF]

BMC Musculoskelet Disord
Patel H, Patel HK, Sharma A, Srivastava S.   +3 more
europepmc   +1 more source

Intelligent-based AT-SHAPF control for enhanced power quality in SOFC-driven hybrid system. [PDF]

Sci Rep
Jagadeesh Y, Kethineni B.
europepmc   +1 more source

Adaptive sliding mode control for chaotic system synchronization using neural networks. [PDF]

Sci Rep
Turab N, Raghu N, Choudhury S, Zkear Abass A, Roslin SE, Kaur G, Pant R, Chauhan G, Khorasanikia Asl A.   +8 more
europepmc   +1 more source

EPIC-NET: EEG-based epilepsy classification and brain localization using Optuna wave-gated recurrent unit network. [PDF]

Front Comput Neurosci
Manjupriya R, Leema AA.
europepmc   +1 more source

Skin cancer recognition by using a neuro-fuzzy system. [PDF]

Cancer Inform, 2011
Salah B, Alshraideh M, Beidas R, Hayajneh F.   +3 more
europepmc   +1 more source

Integrating Artificial Intelligence into Ventilation on Demand: Current Practice and Future Promises. [PDF]

Sensors (Basel)
Chinyadza CR, Risso N, Aramayo A, Momayez M.   +3 more
europepmc   +1 more source

Adaptive neuro-fuzzy control system

, 2000
With the growing interest of using fuzzy logic in our world, adaptive fuzzy logic is keenly researched in the recent decades. One promising way of making fuzzy logic adaptable is to blend it with neural network, which itself is inherently suited to self-learning application. Neural fuzzy systems are frequently used in control applications (Lin and Lee,
openaire   +1 more source