Today, swarm intelligence is widely used in optimization problems. PSO is one the best swarm intelligence methods. In the method, each particle moves toward the direction in which the best individual and group experience has happened. The most important disadvantage of this method is that it falls in local optima. To fix the problem, a metaheuristic method is proposed in this paper. There has a...

Particle swarm optimization is a population based optimization technique that is based on probability rules. In this technique each particle moves toward their best individual and group experience had occurred. Fundamental problems of standard PSO algorithm are the falling into the trap of local optimum and its low speed of convergence. One approach for solving the above problems is to combine ...

Currently there is one of the prevalent diseases of 21st century is liver disorders annually killing so many people’s round the worlds. A range of therapies have been provided by researcher to evaluate results. Early diagnosis is of considerable amount of significance in treating the disease. Diagnosis is of the physician skills conducting based on their knowledge’s and experience yet an error ...

This paper aims to improve the performance of original particle swarm optimization (PSO) so that the consequent method can be more robust and statistically sound for global optimization. A variation of PSO called the orthogonal permutation particle swarm optimization (OPPSO) is presented. An orthogonal permutation strategy, based on the orthogonal experimental design, is developed as a metaboli...

In this study a Dynamically Controlled Particle Swarm Optimization (DCPSO) method has been developed to solve Economic Emission Short-Term Hydrothermal Scheduling (EESTHS) problem of power system with a variety of operational and network constraints. The inertial, cognitive and social behavior of the swarm is modified by introducing exponential functions for better exploration and exploitation ...

Human-robot interfaces for interacting with hundreds of autonomous robots must be very different from single-robot interfaces. The central design challenge is developing techniques to maintain, program, and interact with the robots without having to handle them individually. This requires robots that can support hands-free operation, which drives many other aspects of the design. This paper pre...

In this paper, an effective hybrid algorithm based on Particle Swarm Optimization (PSO) is proposed for solving the Traveling Salesman Problem (TSP), which is a well-known NPcomplete problem. The hybrid algorithm combines the high global search efficiency of fuzzy PSO with the powerful ability to avoid being trapped in local minimum. In the fuzzy PSO system, fuzzy matrices were used to represen...

in this paper, a new enhanced version of the particle swarm optimization (pso) is presented. an important modification is made by adding probabilistic functions into pso, and it is named probabilistic particle swarm optimization (ppso). since the variation of the velocity of particles in pso constitutes its search engine, it should provide two phases of optimization process which are: explorati...

Swarm is a European Space Agency (ESA) project that was launched on 22 November 2013, which consists of three Swarm satellites. Swarm precise orbits are essential to the success of the above project. This study investigates how well Swarm zero-differenced (ZD) reduced-dynamic orbit solutions can be determined using space-borne GPS data and optimized pseudo-stochastic pulses under high ionospher...