This paper presents the application of the PSO (Particle Swarm Optimization) as a tool to solve the Traveling Salesman Problem. The proposed application consists of using a technique based on Artificial Intelligent – AI. It is based in the simulation of social interaction between individuals of a population. Here, each element of population moves in the hyper-space and they are attracted by pos...

Swarm intelligence is a research field that models the collective intelligence in swarms of insects or animals. Many algorithms that simulates these models have been proposed in order to solve a wide range of problems. The Artificial Bee Colony algorithm is one of the most recent swarm intelligence based algorithms which simulates the foraging behaviour of honey bee colonies. In this work, modi...

In order to have clarity in the satellite images we have used Particle Swarm Optimization technique. When incorporated with traditional clustering algorithms, problems such as local optima and sensitivity to initialization, are reduced, thus exploring a greater area using global search. This segmented image is further classified using Kappa coefficient. Keywords— Particle Swarm Optimization(PSO...

In this paper, we introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the signilicant and effective impact of this new parameter on the particle swarm optimizer.

This paper analyses the difficulty of big data analytics problems and the potential of swarm intelligence solving big data analytics problems. Nowadays, the big data analytics has attracted more and more attentions, which is required to manage immense amounts of data quickly. However, current researches mainly focus on the amount of data. In this paper, the other three properties of big data an...

Swarm-intelligence-based and bio-inspired algorithms form a hot topic in the developments of new algorithms inspired by nature. These nature-inspired metaheuristic algorithms can be based on swarm intelligence, biological systems, physical and chemical systems. Therefore, these algorithms can be called swarm-intelligence-based, bio-inspired, physicsand chemistry-based, depending on the sources ...

In this paper we propose neighborhood search (NS) assisted Swarm Intelligence (SI) technique for efficient Multi-input Multi-output (MIMO) receiver. The proposed NS-SI detection method iteratively decodes complex modulation schemes in MIMO system. The simulation results reveal that with this proposed NS-SI detection algorithm near optimal performance is achieved. The performance of proposed det...

Many problems in Ad-Hoc network is divided as an optimization problem such as consumption in energy, localization, routing, use of nodes in effective way. To solve these problems set of routing algorithm have been developed based on swarm intelligence. Ant colony algorithm is based on the behavior of ants in swarm intelligence. To enhance the communication we use different protocols and also lo...

Stochastic Diffusion Search (SDS), first incepted in 1989, belongs to the extended family of Swarm Intelligence algorithms. In contrast to many nature-inspired algorithms, SDS has a strong mathematical framework describing its behaviour and convergence. In addition to concisely exploring the algorithm in the context of natural swarm intelligence systems, this paper reviews the developments of t...

Swarm intelligence theory is proposed for motion planning of multi-robot systems. Multiple particles start from different points in the solutions space and interact to each other while moving towards the goal position. Swarm intelligence theory is a derivative-free approach to the problem of multi-robotcooperation which works by searching iteratively in regions defined by each robot’s best prev...