with the rapid development of the internet, the amount of information and data which are produced, are extremely massive. hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. data mining can overcome this problem. while data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. as the speed of ...

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

this paper proposes per unit coding for combined economic emission load dispatch problem. in the proposed coding, it is possible to apply the percent effects of elements in any number and with high accuracy in objective function. in the proposed per unit coding, each function is transformed into per unit form based on its own maximum value and has a value from 0 to 1. in this paper, particle sw...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

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...

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...

in this paper, the static var compensator (svc) has been used to improve dynamic behaviour of power system. to do this, a new objective function is formulated considering power loss reduction, voltage profile improvement and loadability margin decrease. other contribution of this research is proposing a novel structure for particle swarm optimization (pso) algorithm through modifying the initia...

the issue of unit commitment is one of the most important economic plans in power system. in modern and traditional power systems, in addition to being economical of the planning, the issue of security in unit operation is also of great importance. hence power system operation confronts units’ participation and input considering network security constrains. the issue of units’ participation is ...

this paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (fpso) and fuzzy c-means (fcm) algorithms, to solve the fuzzyclustering problem, especially for large sizes. when the problem becomes large, thefcm algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. the pso algorithm does find ago...

permanent magnet synchronous motors are efficient motors, which have widespread applications in electric industry due to their noticeable features. one of the interesting applications of such motors is in underwater vehicles. in these cases, reaching to minimum volume and high torque of the motor are the major concern. design optimization can enhance their merits considerably, thus reduce volum...