Scope of this analysis is to tune the proportional-integral-derivative (PID) parameters autonomously for controlling the moisture content in the paper industry by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm. The GA and PSO based PID tuning results are compared with the Conventional based PID tuning to examine the performance of time domain specifications; hence,...

The Selective Harmonic Elimination (SHE) technique is the fundamental switching frequency scheme which is used to eliminate specific order harmonics. In this paper, the elimination of low order harmonics in cascaded multilevel inverter with equal DC sources is proposed. The modulation strategy used here is SHEPWM in which non linear equations that characterize the low order harmonics are obtain...

The following paper describes and discusses the suitability of the particle swarm optimization (PSO), of the simulated annealing algorithm (SA) and of the genetic algorithm (GA) for the employment with blind adaptation of the directional characteristic of array antennas. By means of extensive simulations, it was confirmed that the suggested PSO and SA and the improved GA are able to follow dyna...

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...

Optimization is frequently employed in biomechanics research to solve system identification problems, predict human movement, or estimate muscle or other internal forces that cannot be measured directly. Unfortunately, biomechanical optimization problems often possess multiple local minima, making it difficult to find the best solution. Furthermore, convergence in gradient-based algorithms can ...

According to researches, activation was a minor strategy of improving Particle Swarm Algorithm. For proofing the possibility of activation strategy could be a main strategy for improving Particle Swarm Algorithm, this article adopt the concept of mutation in Genetic Algorithm to improve Particle Swarm Optimization. The experimental results show three advantages for the activation strategies. Fi...

Based on introducing two optimization algorithms, group search optimization (GSO) algorithm and particle swarm optimization (PSO) algorithm, a new hybrid optimization algorithm which named particle swarm-group search optimization (PS-GSO) algorithm is presented and its application to optimal structural design is analyzed. The PS-GSO is used to investigate the spatial truss structures with discr...

this study focuses on the forecasting of energy demands of residential and commercial sectors using linear and exponential functions. the coefficients were obtained from genetic and particle swarm optimization (pso) algorithms. totally, 72 different scenarios with various inputs were investigated. consumption data in respect of residential and commercial sectors in iran were collected from the ...

The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

in this paper, we propose a novel algorithm to enhance the noisy speech in the framework of dual-channel speech enhancement. the new method is a hybrid optimization algorithm, which employs the  combination of  the  conventional θ-pso and the shuffled sub-swarms particle optimization (sspso) technique. it is known that the θ-pso algorithm has better optimization performance than standard pso al...