Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian
natural selection. They are popular heuristic optimisation methods based on simulated …

We propose a new quantum-inspired genetic algorithm (QGA) aimed to find the optimal
initial cluster centers of the Fuzzy C-Means (FCM). The quantum chromosomes of the …

In this paper, we propose a multilevel segmentation methods of medical images based on
the classical and quantum genetic algorithms. The Genetic Algorithm (GA) uses a binary …

The fault diagnosis of building electrical systems are of great significance to the safe and
stable operation of modern intelligent buildings. In this paper, it has many problems, such as …

Genetic algorithms are heuristic optimization techniques inspired by Darwinian evolution.
Quantum computation is a new computational paradigm which exploits quantum resources …

Quantum computing appears as an alternative solution for solving computationally
intractable problems. This paper presents a new constrained quantum genetic algorithm …

Genetic algorithms (GAs) are heuristic optimization techniques inspired by Darwinian
evolution, which are characterized by successfully finding robust solutions for optimization …

The dramatic increase of the aging population is a current and primary livelihood issue in
China. It is very important to accurately predict the aging population for policy-makers such …

Quantum genetic algorithms (QGA) are typically built using the traditional representation of
the quantum chromosome in the form of system of independent qubits. This makes it …

In this paper, we present a novel approach for clustering based on quantum genetic
computing and complex systems. The main idea is the use of Wireless Sensor Networks …