A swarm of unmanned aerial vehicles (UAVs) requires the transmission mission-related data across network. The resource constraints and dynamic nature bring critical challenges to design UAV routing protocols. Most conventional ad hoc schemes are not intelligent cannot adapt swarming networks. On other hand, some artificial intelligence (AI)-based may consume significant computational resources ...

The purpose of protein-protein interaction network clustering is to find major modules for cells function. Various clustering algorithms are used but only some of them take advantage of intelligent computational methods. In this work we introduced a particle swarm optimization method to find dense sub-graphs in protein-protein interaction networks. The experimental results proved that our metho...

We present a novel application of the Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on the intelligent foraging behavior of honey bees. We present a 2-level metaheuristic approach where an Artificial Bee Colony Algorithm acts as a low-level metaheuristic and its paremeters are se...

This paper presents an intelligent method of tuning a flat controller for trajectory tracking of a single link flexible manipulator. The tip position of the manipulator was determined as the flat output. Using the flat output, a feedback control law is designed to stabilize the tip of the end effector and track the reference trajectories. The gains obtained for the flat controller is optimized ...

Rapid growth in the Internet usage and diverse military applications have led researchers to think of intelligent systems that can assist the users and applications in getting the services by delivering required quality of service in networks. Some kinds of intelligent techniques are appropriate for providing security in communication pertaining to distributed environments such as mobile comput...

This paper attempts to bring forward various newly emerged natural computing techniques to a common platform. Six such techniques are compared among each other which have been used to solve a w ell known classical problem, the travelling salesman problem. The techniques discussed in this paper are Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Optimization ...

The new type of Mobile Ad hoc Network which is called Vehicular Ad hoc Networks (VANET) created a fertile environment for research. In this research, a protocol Particle Swarm Optimization Contention Based Broadcast (PCBB) is proposed, for fast and effective dissemination of emergency messages within a geographical area to distribute the emergency message and achieve the safety system, this res...

<p>The neural network runs slowly and lacks accuracy in power load forecasting, so it is optimized using meta-heuristic algorithm. Salp Swarm Algorithm (SSA) a novel algorithm that simulates the salp foraging process. In this paper, parallel swarm (PSSA) proposed to improve performance of SSA. It not only improves local development capabilities, but also accelerates global exploration. Th...

Abstract Electrical engineering is closely related to people’s life. Many projects have proved that electrical using PSO algorithm provides more convenient applications for production and life, greatly improves living standards, makes life work relaxed valid. In many fields, such as subway engineering, if advanced automation adopted, the can be carried out validly from start finish, workload of...

Swarm intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. Particle swarm, Ant colony, Bee colony are examples of swarm intelligence. In the field of computer science and operations research, Artificial Bee Colony Algorithm (ABC) is an optimization algorithm based on the intelligent foraging behavio...