The particle swarm, which optimizes neural networks, has overcome its disadvantage of slow convergent speed and shortcoming of local optimum. The parameter that the particle swarm optimization relates to is not much. But it has strongly sensitivity to the parameter. In this paper, we applied PSO-BP to evaluate the environmental effect of an agricultural project, and researched application and P...

Particle swarm Optimization (PSO) is mainly inspired by social behavior patterns of organisms that live and interact within large groups. The term PSO refers to a relatively new family of algorithms that is used to find optimal or near to optimal solutions to numerical and qualitative problems. It is an optimization paradigm that simulates the ability of human to process knowledge. The capabili...

The standard optimized link state routing (OLSR) introduces an interesting concept, the multipoint relays (MPRs), to mitigate message overhead during the flooding process. This paper propose a new algorithm for MPRs selection to enhance the performance of OLSR using particle swarm optimization sigmoid increasing inertia weight (PSOSIIW). The sigmoid increasing inertia weight has significance im...

This paper presents a designing an optimal adaptive controller for tracking down the control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been used to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using a logic is proposed to increase the c...

In this paper, a feedback learning particle swarm optimization algorithm with quadratic inertia weight (FLPSOQIW) is developed to solve optimization problems. The proposed FLPSO-QIW consists of four steps. Firstly, the inertia weight is calculated by a designed quadratic function instead of conventional linearly decreasing function. Secondly, acceleration coefficients are determined not only by...

Since the aerobics is introduced into the college and university, it becomes popular in teachers and students. In order to develop the aerobics better and improve the level of the aerobics, it is necessary to predict the aerobics performance. Support vector machine method is one of the frequently-used prediction methods. In order to improve the performance of traditional LS-SVM, we put forward ...

It is difficult to distinguish the independent effects of gravity from those of inertia on a running animal. Simply adding mass proportionally changes both the weight (gravitational force) and mass (inertial force) of the animal. We measured ground reaction forces for eight male humans running normally at 3 m s(-)(1) and under three experimental treatments: added gravitational and inertial forc...

The particle swarm optimization algorithm (PSO) is a meta-heuristic with intelligence. It has the advantages of easy implementation, high convergence accuracy, and fast speed. However, PSO suffers from falling into local optimum or premature convergence, better performance desired. Some methods adopt improvements in parameters, initialization, topological structure to enhance global search abil...