The only objective of programming is not to determine the algorithm to accomplish a result, but relevance and correctness of the result also need to be ascertained. Correctness can be insured by applying testing to the result. Testing is most critical practice which is performed for supporting quality assurance. It is substantial but also arduous to warrant the quality of software; half of the ...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...

in this paper, the fuzzy system has been used for fault detection and diagnosis of a yeast fermentation bioreactor based on measurements corrupted by noise. in one case, parameters of membership functions are selected in a conventional manner. in another case, using certainty factors between normal and faulty conditions the optimal values of these parameters have been obtained through the genet...

oil production optimization is one of the main targets of reservoir management. smart well technology gives the ability of real time oil production optimization. although this technology has many advantages; optimum adjustment or sizing of corresponding valves is still an issue to be solved. in this research, optimum port sizing of inflow control devices (icds) which are passive control valves ...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

In this work, a Genetic Algorithm boosted Least Square Support Vector Machine model by a set of linear equations instead of a quadratic program, which is improved version of Support Vector Machine model, was used for estimation of 98 pure compounds second virial coefficient. Compounds were classified to the different groups. Finest parameters were obtained by Genetic Algorithm method ...

Image segmentation is a significant step in any computer vision system. It can be explore as a process of isolating objects of interest from the rest of the scene. In this paper, we propose a new threshold based information parameter for image segmentation through Genetic Algorithm. We used Genetic Algorithm because it is able to determine the optimal number of regions of segmentation. The deve...

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...

Based on 3-D elasticity approach, differential quadrature method (DQM) in axial direction is adopted along with Globalized Nelder–Mead (GNM) algorithm to optimize the stacking sequence of a laminated cylindrical shell. The anisotropic cylindrical shell has finite length with simply supported boundary conditions. The elasticity approach, combining the state space method and DQM is used to obtain...

the traveling salesman problem (tsp) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. the tsp is probably the most famous and extensively studied problem in the field of combinatorial optimization. because this problem is an np-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...