Abstract Formation flight of unmanned aerial vehicles (UAVs) utilizes reconfiguration procedures to handle a variety emergencies, such as collision avoidance, malfunctions, fuel savings, and member replacement. As UAVs have limited computing power energy resources, it is necessary optimize the control inputs reduce distance travelled by while reducing costs during formation reconfiguration. In ...

The quality of information extracted from the vibration signals, and accuracy bearing status detection depend on methods used to process signal select informative features. In this paper, a new hybrid approach is introduced in which relatively swarm decomposition (SWD) method optimized compensation distance evaluation technique (OCDET) are enhance processing stage improve optimal features selec...

This study presents a robust and rigorous method based on intelligent models, namely radial basis function networks optimized by particle swarm optimization (PSO-RBF), multilayer perceptron neural networks (MLP-NNs), and adaptive neuro-fuzzy inference system optimized by particle swarm optimization methods (PSO-ANFIS), for predicting the equilibrium and kinetics of the adsorption of sulfur and ...

One of the major motifs in collective or swarm intelligence is that, even though individuals follow simple rules, the resulting global behavior can be complex and intelligent. In artificial swarm systems, such as swarm robots, the goal is to use systems that are as simple and cheap as possible, deploy many of them, and coordinate them to conduct complex tasks that each individual cannot accompl...

This paper is based on swarm intelligence and chaotic dynamics for learning. We address this issue by considering the problem of path planning for mobile robots. Autonomous systems assume intelligent behavior with ability of dealing in complex and changing environments. Path planning problem, which can be studied as an optimization problem, seems to be of high importance for arising of intellig...

Orthogonal Frequency Division Multiplexing (OFDM) has the inherent properties of being robust to interference and frequency selective fading and is de facto the adopted multiplexing techniques for the 4 th generation wireless network systems. In wireless system, resources such as bandwidth and power are limited, intelligent allocation of these resources to users are crucial for delivering the b...

The swarm intelligence of animals is a natural paradigm to apply to optimization problems. Ant colony, bee colony, firefly and bat algorithms are amongst those that have been demonstrated to efficiently to optimize complex constraints. This paper proposes the new Sparkling Squid Algorithm (SSA) for multimodal optimization, inspired by the intelligent swarm behavior of its namesake. After an int...

This paper surveys the intersection of two fascinating and increasingly popular domains: swarm intelligence and optimization. Whereas optimization has been popular academic topic for decades, swarm intelligence is relatively new subfield of artificial intelligence which studies the emergent collective intelligence of groups of simple agents. It is based on social behavior that can be observed i...

Particle Swarm Optimisation (PSO) is an intelligent search method based on swarm intelligence and has been widely used in many fields. However it is also easily trapped in local optima. In this paper, we propose two hybrid PSO algorithms: one uses a Differential Evolution (DE) operator to replace the standard PSO method for updating a particle’s position; and the other integrates both the DE op...