recently, increasing attention has been directed to the isolation of natural active components from various medicinal plants. in the present research, the extraction of essential oil from horehound (m. vulgare l.) is presented. effects of mass ratio and particle size on the process performance were studied and kinetics were determined. the chemical composition of the volatiles present in m. vul...

In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...

crack identification is a very important issue in mechanical systems, because it is a damage that if develops may cause catastrophic failure. in the first part of this research, modal analysis of a multi-cracked variable cross-section beam is done using finite element method. then, the obtained results are validated usingthe results of experimental modal analysis tests. in the next part, a nove...

In view of the shortcomings of the test data generation algorithm including particle swarm optimization algorithm and ant colony algorithm, a new algorithm is proposed, which is based on the combination of particle swarm algorithm and parameter adjustment. This algorithm can dynamically adjust its search capabilities based on the fitness value of particles , combine the advantages of particle s...

the improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. detailed examination of changes in expression levels of genes can help physicians to have effi cient diagnosing, classification of tumors and cancer’s types as well as effective treatments. finding genes that can classify the group of...

This paper proposes a novel optimization algorithm combined the mechanism of quantum evolutionary algorithm and real-coding method, called an improved quantum particle swarm optimization algorithm (IQPSO). Like the traditional particle swarm optimization, IQPSO is also characterized by position vector and velocity vector to implement the evolution process. However, the particle of IQPSO is divi...

An improved particle swarm optimization algorithm, which combines the idea of simulated annealing algorithm and opposition-based learning strategy, is presented for NP-hard protein structure prediction based on AB model. Flying grain is used to control the neighborhood structure of particle, so particle can search the global optimum in solution space more finely. An opposition-based learning is...

Population based metaheuristics are commonly used for global optimization problems. These techniques depend largely on the generation of initial population. A good initial population may not only result in a better fitness function value but may also help in faster convergence. Although these techniques have been popular since more than three decades very little research has been done on the in...

Seas and oceans are the most important sources of renewable energy in the world. The main purpose of this paper is to use an appropriate control strategy to improve the performance of point absorbers. In this scheme, considering the high uncertainty in the parameters of the power take-off system in different atmospheric conditions, a new improved black hole algorithm is introduced to tune fuzzy...