Abstract Knowledge extraction through machine learning techniques has been successfully
applied in a large number of application domains. However, apart from the required …

The rapid development of quantum computer hardware has laid the hardware foundation for
the realization of QNN. Due to quantum properties, QNN shows higher storage capacity and …

The field of artificial neural networks is expected to strongly benefit from recent
developments of quantum computers. In particular, quantum machine learning, a class of …

Fault diagnosis for aircraft fuel system can not only improve flight security, but also reduce
the huge cost due to regular maintenance. It remains a problem because of the complicated …

In this paper, a neural networks model for quantum computer is proposed. The core of this
model is quantum neuron. Firstly, the inner product of the input qubits and the weight qubits …

摘要机器学习在过去十几年里不断发展, 并对其他领域产生了深远的影响. 近几年,
研究人员发现结合量子计算特性的新型机器学习算法可实现对传统算法的加速 …

Quantum machine learning can play an essential role in smart manufacturing applications.
This paper aimed to understand the state of the art of quantum computing in machine …

The ability of artificial neural networks (ANNs) to adapt to input data and perform
generalizations is intimately connected to the use of nonlinear activation and propagation …

This paper presents the HybriD-GM model conception, from modeling to consolidation. The
D-GM environment is also extended, providing efficient parallel executions for quantum …

The advent of quantum computers has justified the development of quantum machine
learning algorithms, based on the adaptation of the principles of machine learning to the …