New approaches of particle swarm optimisation algorithm based on Gaussian and Cauchy distributions to adjust the control points of B-spline neural networks are proposed. B-spline networks are trained by gradient-based methods, which may fall into local minimum during the learning procedure. To overcome the problems encountered by the conventional learning methods, particle swarm optimisation  ...

In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize machining parameters in hard turning processes where multiple conflicting objectives are present. The relationships between machining parameters and the performance measures of interest are obtained by using experimental data and swarm intelligent neural network systems (SINNS)....

Power system component fault diagnosis problem is a key issue in case of the failure of the power system. A Bayesian network, in which the network parameters are learnt by a particle swarm optimization algorithm, is proposed in this paper to establish the statistical diagnosis model. The Noisy-Or and Noisy-And structure are employed to construct the framework of the model, where the 4-level Bay...

In this paper we present a distributed algorithm, which enables to follow and surround moving objects by a swarm of homogenous robots that only use local sensing. We introduce the multi orbit surrounding problem and present a solution for it. We prove that our solution always guarantees that the robots enclose the target and circulate around them. We also evaluate our solution by simulations.

PSO algorithm is an intelligent optimization algorithm based on swarm intelligence. Particle swarm optimization algorithm is simple, easy to implement, and it has a wide application prospect in scientific research and engineering applications. In real life, most of the optimization problem is the optimization problem of some nonlinear discrete with the existence of local. PSO algorithm also has...

This paper proposes an algorithm for Public Key Cryptography (PKC) using the hybrid concept of two evolutionary algorithms, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) respectively. PSO alone are fast and easy to implement, they follow the procedures of common evolutionary algorithm and posses memory feature which is absent in GA making it more valuable. In GA whole population ...

Swarm intelligence is the technological modeling of behaviors of social insects, such as the ant or the honeybee. Although each element comprising swarm intelligence is simple, high grade intelligence emerges when the elements gather to form a swarm. Ant Colony Optimization (Dorigo, M, et al., 1997), which is called ACO, is one of the swarm intelligence and has been attracting much attention re...

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow ap...

In this paper, the idea of a new artificial intelligence based optimization algorithm, which is inspired from the nature of vortex, has been provided briefly. As also a bio-inspired computation algorithm, the idea is generally focused on a typical vortex flow / behavior in nature and inspires from some dynamics that are occurred in the sense of vortex nature. Briefly, the algorithm is also a sw...

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that ha...