This paper presents the performance of Integrated Bacterial Foraging Optimization and Particle Swarm Optimization (IBFO_PSO) technique in MANET routing. The BFO is a bioinspired algorithm, which simulates the foraging behavior of bacteria. It is effectively applied in improving the routing performance in MANET. In results, it is proved that the PSO integrated with BFO reduces routing delay, ene...

In recent years, Particle Swarm Optimization has evolved as an effective global optimization algorithm whose dynamics has been inspired from swarming or collaborative behavior of biological populations. In this paper, PSO has been applied to Triple Link Inverted Pendulum model to find its reduced order model by minimization of error between the step responses of higher and reduced order model. ...

Test Effort Estimation is an important activity in software development. The test effort can be calculated on the basis of effort cost and time required for testing. Several studies have been done for developing test effort estimation models but to some extent only, most of these models result in erroneous results. So there is a strong need to optimize the efforts estimated. Meta heuristic tech...

Inspired by the migratory behavior in the nature, a novel particle swarm optimization algorithm based on particle migration (MPSO) is proposed in this work. In this new algorithm, the population is randomly partitioned into several sub-swarms, each of which is made to evolve based on particle swarm optimization with time varying inertia weight and acceleration coefficients (LPSO-TVAC). At perio...

Particle swarm optimization is a population-based algorithm and used for optimization in a wide range of problems. In this article, a method that is called Hybrid Particle Swarm Optimization or HPSO is proposed. It is composed of some versions of particle swarm optimization algorithms, which have subgroups in their structures. They are DMS-PSO, PS2OS and MCPSO. In fact, a hierarchical structure...

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The p...

A dynamic organizational adjustment particle swarm optimization-based particle filter algorithm (OAPSO-PF) is presented in this paper in order to solve the problem of low precision and complicated calculation of particle filter based on particle swarm optimization algorithm(PSO-PF). Through the mutual competition and collaboration among organizations, this algorithm allows the particles to adap...

In this work, we suggest that the poorer results obtained with particle swarm optimization (PSO) in some previous studies should be attributed to the cross-validation scheme commonly employed to improve generalization of PSO-trained neural network river forecasting (NNRF) models. Crossvalidation entails splitting the training dataset into two, and accepting particle position updates only if fit...

this paper, presents a suitable control system to manage energy in distributed power generation system with a battery energy storage station and fuel cell. first, proper dynamic shape modeling is prepared. second, control system is proposed which is based on classic controller. this model is educated with genetic algorithm and particle swarm optimization. the proposed strategy is compared with ...