The gravitational search algorithm (GSA) is a kind of swarm intelligence optimization algorithm based on the law of gravitation. The parameter initialization of all swarm intelligence optimization algorithms has an important influence on the global optimization ability. Seen from the basic principle of GSA, the convergence rate of GSA is determined by the gravitational constant and the accelera...

In recent years large number of algorithms based on the swarm intelligence has been proposed by various researchers. The Artificial Bee Colony (ABC) algorithm is one of most popular stochastic, swarm based algorithm proposed by Karaboga in 2005 inspired from the foraging behavior of honey bees. In short span of time, ABC algorithm has gain wide popularity among researchers due to its simplicity...

Traditional mathematical algorithms are incapable of solving real time engineering design problems because of its rigid procedure mainly due to discrete or random data and multiobjective functions in a problem. An optimization algorithm is a procedure which is executed iteratively by comparing various solutions till the optimum or a satisfactory solution is found. There are two population based...

Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. Particle swarm optimization is an optimization method. It is an optimization algorithm, which is based on swarm intelligence. Optimization problems are widely used in different fields of...

As a model used for parameter estimation, BP neural network has remarkable effect in many prediction algorithms. However, there are situations that will fall into the local optimal solution and learning speed is slow. To solve these two problems, this paper combines dynamic adaptive strategy genetic algorithm, method of eliminating honey sources bee colony greedy ant introduction variation oper...

Swarming algorithms usually require fast and reliable local information distribution among neighbouring nodes. Additionally, many applications also require global information distribution in the shortest possible time. We show that communication links with a range which is small compared to the size of the swarm offer many advantages. We propose a system using low frequency radio communication ...

This paper presents a novel image segmentation algorithm, which uses a biologically inspired paradigm known as swarm intelligence to segment images. A more efficient MRF based clustering algorithm that incorporated the Markov Random Field (MRF) theory and the Quantum Particle Swarm Optimization (QPSO) algorithm is proposed. the QPSO algorithm is ised to optimize the energy function which is a c...

Swarm Intelligence is the emergent collective intelligence of groups of simple agents acting almost independently. Algorithms following this paradigm have many desirable properties: flexibility, decentralized control, robustness, and fault tolerance. This paper presents a novel agent coordination model inspired by the way ants collectively transport large preys. In our model a swarm of agents, ...