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 ...

In this paper, echo cancellation is done using genetic algorithm (GA). The genetic algorithm is implemented by two kinds of crossovers; heuristic and microbial. A new procedure is proposed to estimate the coefficients of adaptive filters used in echo cancellation with combination of the GA with Least-Mean-Square (LMS) method. The results are compared for various values of LMS step size and diff...

normal 0 false false false en-us x-none fa background:  regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. the method of segmentation is used to analyze anal to miscall structures in medical imaging. objective:  this study describes a new method for brain magnetic resonance image (mri) segmentation via a ...

This paper introduces the optimization algorithm to improve search rate in urban path routing problems using viral infection and local search in urban environment. This algorithm operates based on two different approaches including wavelet transform and genetic algorithm. The variables proposed by driver such as degree of difficulty and difficulty traffic are of the essence in this technique. W...

in this paper, a method based on binary-coded genetic algorithm is proposed to explore an optimization method, for obtaining an optimal elliptical tank. this optimization method enhances the rollover threshold of a tank vehicle, especially under partial filling conditions. minimizing the overturning moment imposed on the vehicle due to c.g. height of the liquid load, lateral acceleration and ca...

this paper proposes an optimized control policy over type one diabetes. type one diabetes is taken into consideration as a nonlinear model (augmented minimal model), which is implemented in matlab-simulink. this model is developed in consideration of the patient's conditions. there are some uncertainties in the regarded model due to factors such as blood glucose concentration, daily meals ...

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...

the mathematical modeling of fracture networks is critical for the exploration and development ofnatural resources. fractures can help the production of petroleum, water, and geothermal energy. theyalso greatly influence the drainage and production of methane gas from coal beds. orientation andspatial distribution of fractures in rocks are important factors in controlling fluid flow. the object...