Quantum neural network is a useful tool which has seen more development over the years mainly after twentieth century. Like artificial neural network (ANN), a novel, useful and …
H Kou, Y Zhang, HP Lee - Computers & Structures, 2024 - Elsevier
Solving dynamic optimization problems (DOPs) induced by time-varying optimization objective functions and constraints is challenging. Quantum computation has received …
S Ganjefar, AA Ghassemi, MM Ahmadi - Energy, 2014 - Elsevier
In this paper, a quantum neural network (QNN) is used as controller in the adaptive control structures to improve efficiency of the maximum power point tracking (MPPT) methods in the …
This paper makes an exhaustive survey of various applications of Quantum inspired computational intelligence (QCI) techniques proposed till date. Definition, categorization and …
N Kouda, N Matsui, H Nishimura, F Peper - Neural Computing & …, 2005 - Springer
Neural networks have attracted much interest in the last two decades for their potential to realistically describe brain functions, but so far they have failed to provide models that can …
The classical self-supervised neural network architectures suffer from slow convergence problem and incorporation of quantum computing in classical self-supervised networks is a …
XZ Li, WW Chen, YQ Wang - International Journal of Theoretical Physics, 2018 - Springer
To obtain higher encryption efficiency and to realize the compression of quantum image, a quantum gray image encryption-compression scheme is designed based on quantum …
MM Zirkohi - Applied Soft Computing, 2022 - Elsevier
In this work, an efficient robust control scheme is proposed for position control of induction motors based on field-oriented control (FOC). The proposed control scheme consists of …