نتایج جستجو برای: evolutionary algorithm

تعداد نتایج: 855248  

Journal: :journal of advances in computer research 0

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA ...

The purpose of this article is to review the literature on the topic of deterministic vehicle routing problem (VRP) and to give a review on the exact and approximate solution techniques. More specifically the approximate (meta-heuristic) solution techniques are classified into: tabu search, simulated annealing, genetic algorithm, evolutionary algorithm, hybrid algorithm, and Ant Colony Opti...

K.N.V. Chandrasekhar, N.S.S. Sahithi

Topology optimization has been an interesting area of research in recent years.  The main focus of this paper is to use an evolutionary swarm intelligence algorithm to perform Isogeometric Topology optimization of continuum structures.  A two-dimensional plate is analyzed statically and the nodal displacements are calculated.  The nodal displacements using Isogeometric analysis are found to be ...

Journal: :Egyptian Informatics Journal 2021

A novel evolutionary algorithm called learner performance based behavior (LPB) is proposed in this article. The basic inspiration of LPB originates from the process accepting graduated learners high school different departments at university. In addition, changes those should do their studying behaviors to improve study level most important stages optimization; exploitation and exploration are ...

There are various automatic programming models inspired by evolutionary computation techniques. Due to the importance of devising an automatic mechanism to explore the complicated search space of mathematical problems where numerical methods fails, evolutionary computations are widely studied and applied to solve real world problems. One of the famous algorithm in optimization problem is shuffl...

Amin Rastegar Pour, Hassan Barati,

Abstract: One of the equipment that can help improve distribution system status today and reduce the cost of fault time is remote control switches (RCS). Finding the optimal location and number of these switches in the distribution system can be modeled with various objective functions as a nonlinear optimization problem to improve system reliability and cost. In this article, a particle swarm ...

Journal: :international journal of civil engineering 0
mostafa khanzadi tehran, narmak, iust, civil engineering dept. seyed mehdi tavakkoli iran university of science and technology

an evolutionary structural optimization (eso) method is used for plastic design of frames. based on safe theorems some criteria are derived and made an effort to satisfy them during the optimization process. in this regard, equilibrium is checked and yield condition is gradually satisfied during the optimization process. in this method, the amount of used material and the stiffness for each ele...

Journal: :journal of computer and robotics 0
seyed mahmood hashemi school of computer engineering, darolfonoon high educational institute, qazvin, iran

fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. in this research, fcm is chosen for fuzzy clustering. parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. these two parameters require tuning to reduce the overfitting in the...

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