In this paper, artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for the modelling and simulation of quantum-dot cellular automata (QCA) circuits. For this purpose, all QCA basis components and gates are modelled using ANN and ANFIS. The accuracy and performance of the proposed methods are analysed through a few circuits. Finally, we compared the simulation speed of the proposed methods with QCADesigner software. The results show that the proposed ANN and ANFIS models are much faster than QCADesigner. Also, these models are imported into HSPICE software to design and simulate complex QCA logic circuits.
